bluuebunny/crossref_metadata_2025 huggingface dataset:
Sequenzvarianten unklarer Signifikanz bei Small-Fiber-Neuropathie
Authors: Meyer zu Altenschildesche Caren , Egenolf Nadine , Lischka Annette , Üçeyler Nurcan
Published: May 2024

Hintergrund

Bei etwa der Hälfte der PatientInnen mit Small-Fiber-Neuropathie (SFN) findet sich für die Schmerzsymptomatik keine erklärende und behandelbare Ätiologie. Es häufen sich Berichte zu genetisch-neuropathischen Schmerzsyndromen. Auch einige SFN-PatientInnen weisen Variationen in schmerzassoziierten Genen auf. Teils sind diese bereits als „pathogen“ bestätigt, andere haben eine „unklare pathogenetische Relevanz“. Trotz des hohen Anteils betroffener PatientInnen ist über die genetische SFN bislang wenig bekannt.

Fragestellung

In unserer Arbeit fokussierten wir uns auf diese Kohorte: Durch Sammlung klinischer Daten sollten Charakteristika der PatientInnen mit seltenen Varianten unklarer Signifikanz in schmerzassoziierten Genen gesammelt werden.

Material und Methoden

Von 2015 bis 2020 untersuchten wir 66 PatientInnen mit initial „idiopathischer“ SFN. Bei 13/66 (20 %) wurden Varianten unklarer pathogenetischer Relevanz in schmerzassoziierten Genen detektiert. Alle rekrutierten PatientInnen unterzogen sich einer detaillierten Anamneseerhebung mit Fokus auf Schmerz und beantworteten Fragebögen zu Beschwerden und Belastung.

Ergebnisse

Die Kohorte mit seltener Variante in schmerzassoziierten Genen zeigte gegenüber den anderen PatientInnen subtile klinische Unterschiede: Neben einer höheren physischen und psychischen Belastung konnten eine von außen beeinflussbare Symptomatik und eine herausfordernde Therapie nachgewiesen werden.

Diskussion

Wir sehen eine frühzeitige genetische Diagnostik bei SFN als essenziell: Durch weitere supportive Maßnahmen wie Vermeidung von Einflussfaktoren, Stärkung der Resilienz und eventuell künftig verfügbare zielgerichtete Therapeutika kann die Versorgung der PatientInnen mit seltener Variante in schmerzassoziierten Genen optimiert werden.
Short-term multi-step-ahead sector-based traffic flow prediction based on the attention-enhanced graph convolutional LSTM network (AGC-LSTM)
Authors: Zhang Ying , Xu Shimin , Zhang Linghui , Jiang Weiwei , Alam Sameer , Xue Dabin
Published: May 2024

Accurate sector-based air traffic flow predictions are essential for ensuring the safety and efficiency of the air traffic management (ATM) system. However, due to the inherent spatial and temporal dependencies of air traffic flow, it is still a challenging problem. To solve this problem, some methods are proposed considering the relationship between sectors, while the complicated spatiotemporal dynamics and interdependencies between traffic flow of route segments related to the sector are not taken into account. To address this challenge, the attention-enhanced graph convolutional long short-term memory network (AGC-LSTM) model is applied to improve the short-term sector-based traffic flow prediction, in which spatial structures of route segments related to the sector are considered for the first time. Specifically, the graph convolutional networks (GCN)-LSTM network model was employed to capture spatiotemporal dependencies of the flight data, and the attention mechanism is designed to concentrate on the informative features from key nodes at each layer of the AGC-LSTM model. The proposed model is evaluated through a case study of the typical enroute sector in the central–southern region of China. The prediction results show that MAE reduces by 14.4% compared to the best performing GCN-LSTM model among the other five models. Furthermore, the study involves comparative analyses to assess the influence of route segment range, input and output sequence lengths, and time granularities on prediction performance. This study helps air traffic managers predict flight situations more accurately and avoid implementing overly conservative or excessively aggressive flow management measures for the sectors.
A novel artificial intelligence-based endoscopic ultrasonography diagnostic system for diagnosing the invasion depth of early gastric cancer
Authors: Uema Ryotaro , Hayashi Yoshito , Kizu Takashi , Igura Takumi , Ogiyama Hideharu , Yamada Takuya , Takeda Risato , Nagai Kengo , Inoue Takuya , Yamamoto Masashi , Yamaguchi Shinjiro , Kanesaka Takashi , Yoshihara Takeo , Kato Minoru , Yoshii Shunsuke , Tsujii Yoshiki , Shinzaki Shinichiro , Takehara Tetsuo
Published: May 2024

Background

We developed an artificial intelligence (AI)-based endoscopic ultrasonography (EUS) system for diagnosing the invasion depth of early gastric cancer (EGC), and we evaluated the performance of this system.

Methods

A total of 8280 EUS images from 559 EGC cases were collected from 11 institutions. Within this dataset, 3451 images (285 cases) from one institution were used as a development dataset. The AI model consisted of segmentation and classification steps, followed by the CycleGAN method to bridge differences in EUS images captured by different equipment. AI model performance was evaluated using an internal validation dataset collected from the same institution as the development dataset (1726 images, 135 cases). External validation was conducted using images collected from the other 10 institutions (3103 images, 139 cases).

Results

The area under the curve (AUC) of the AI model in the internal validation dataset was 0.870 (95% CI: 0.796–0.944). Regarding diagnostic performance, the accuracy/sensitivity/specificity values of the AI model, experts (n = 6), and nonexperts (n = 8) were 82.2/63.4/90.4%, 81.9/66.3/88.7%, and 68.3/60.9/71.5%, respectively. The AUC of the AI model in the external validation dataset was 0.815 (95% CI: 0.743–0.886). The accuracy/sensitivity/specificity values of the AI model (74.1/73.1/75.0%) and the real-time diagnoses of experts (75.5/79.1/72.2%) in the external validation dataset were comparable.

Conclusions

Our AI model demonstrated a diagnostic performance equivalent to that of experts.
An update on tests used for intraoperative monitoring of cognition during awake craniotomy
Authors: de Zwart Beleke , Ruis Carla
Published: May 2024

Purpose

Mapping higher-order cognitive functions during awake brain surgery is important for cognitive preservation which is related to postoperative quality of life. A systematic review from 2018 about neuropsychological tests used during awake craniotomy made clear that until 2017 language was most often monitored and that the other cognitive domains were underexposed (Ruis, J Clin Exp Neuropsychol 40(10):1081–1104, 218). The field of awake craniotomy and cognitive monitoring is however developing rapidly. The aim of the current review is therefore, to investigate whether there is a change in the field towards incorporation of new tests and more complete mapping of (higher-order) cognitive functions.

Methods

We replicated the systematic search of the study from 2018 in PubMed and Embase from February 2017 to November 2023, yielding 5130 potentially relevant articles. We used the artificial machine learning tool ASReview for screening and included 272 papers that gave a detailed description of the neuropsychological tests used during awake craniotomy.

Results

Comparable to the previous study of 2018, the majority of studies (90.4%) reported tests for assessing language functions (Ruis, J Clin Exp Neuropsychol 40(10):1081–1104, 218). Nevertheless, an increasing number of studies now also describe tests for monitoring visuospatial functions, social cognition, and executive functions.

Conclusions

Language remains the most extensively tested cognitive domain. However, a broader range of tests are now implemented during awake craniotomy and there are (new developed) tests which received more attention. The rapid development in the field is reflected in the included studies in this review. Nevertheless, for some cognitive domains (e.g., executive functions and memory), there is still a need for developing tests that can be used during awake surgery.
Conjunctive surface water and groundwater management in a multiple user environment
Authors: Zhang Z. Y. , Sato M.
Published: May 2024

The conjunctive use of surface water and groundwater is practiced worldwide as a measure to address water supply uncertainty. This paper focuses on a scenario in which an aquifer is open to multiple users and examines the impact of such an open-access environment on the stabilization function of conjunctive management. We construct a non-cooperative stochastic dynamic game model where multiple users utilize groundwater intake from a common aquifer as a complement to fluctuating surface water. We also propose a simpler baseline applicable to dynamic environments to compute the benefits of the stabilization function when users are unable to adjust groundwater intake to surface water uncertainties. We then apply the model to the real-world case of the water supply environment of the Cao’e River in China. Simulation results show that open access leads to diminishing stabilization values as higher pumping costs due to declining stocks lead to a weakening of users’ incentive to utilize groundwater flexibly. Furthermore, the stabilization function itself is destabilized as the number of users increases. This is because greater groundwater intake and a decline in stocks amplify variations in pumping costs caused by different patterns of surface-water fluctuation.
Gilles de la Tourette syndrome as a rare co-morbidity of Klinefelter syndrome
Authors: Cavanna Andrea E. , Paini Giulia , Purpura Giulia , Riva Anna , Nacinovich Renata , Seri Stefano
Published: May 2024

Background

Klinefelter syndrome (47, XXY) is the most common sex chromosome aneuploidy. In addition to male hypergonadotropic hypogonadism, a wide range of neurodevelopmental disorders, anxiety and affective symptoms have been reported in a substantial proportion of cases.

Case description

We document the rare case of a 43-year-old man diagnosed with Klinefelter syndrome and co-morbid Gilles de la Tourette syndrome. He presented with multiple motor and vocal tics since adolescence, as well as anxiety and affective symptoms as his main tic-exacerbating factors. Tic severity was rated as marked (Yale Global Tic Severity Scale score of 78/100), and recommendations for the treatment of both tics and psychiatric co-morbidities were formulated.

Discussion

Neurodevelopmental tics in the context of Klinefelter syndrome have been previously documented in three cases only. Gilles de la Tourette syndrome is 3–4 times more common in males than females and its etiological factors include multiple genetic components (genetic heterogeneity). Our case report widens the spectrum of neurodevelopmental disorders observed in the context of Klinefelter syndrome and contributes to genetic research on the role of the X chromosome in the pathophysiology of tic disorders.
Teaching advanced technology (ADAS) and use of touch screens in driver training in Norway
Authors: Saetren Gunhild Birgitte , Vaag Jonas Rennemo , Saghafian Mina , Wigum Jan Petter , Helde Roger
Published: May 2024

As many as 4,601 people were injured or killed on the roads in Norway in 2022. This number is too high and highlights the necessity of putting road safety on the agenda. The car industry today is represented by a vast increase in advanced technology for drivers to interact with, and knowing how and when to use this technology is crucial for safe driving. Thus, our research question was: Does the Norwegian driver training industry teach advanced driver assistance technology (ADAS) and touch screens in their driver training?

A survey was distributed to 1,058 driving schools in Norway, resulting in 333 responses. The results showed that driving instructors spend considerably more effort on teaching inbuilt driving assist technologies that enhance driving safety than on those that are designed to enhance safety but that, if not understood well, could lead to hazardous outcomes. Suggestions on how to improve driver training and driving instructor education are made. Research and practical implications are presented to make sure that driving education is updated and aligned with technological advancements in the automobile industry and to ensure traffic safety for all road users.
A proposed stratification system to address the heterogeneity of Subdural Hematoma Outcome reporting in the literature
Authors: Nisson Peyton L. , Francis John , Michel Michelot , Maeda Takuma , Patil Chirag
Published: May 2024

A major challenge within the academic literature on SDHs has been inconsistent outcomes reported across studies. Historically, patients have been categorized by the blood-product age identified on imaging (i.e., acute, subacute, or chronic). However, this schematic has likely played a central role in producing the heterogeneity encountered in the literature. In this investigation, a total of 494 patients that underwent SDH evacuation at a tertiary medical center between November 2013-December 2021 were retrospectively identified. Mechanism of injury was reviewed by the authors and categorized as either positive or negative for a high-velocity impact (HVI) injury. Any head strike injury leading to the formation of a SDH while traveling at a velocity beyond that of normal locomotion or daily activities was categorized as an HVI. Patients were subsequently stratified by those with an acute SDHs after a high-velocity impact (aSDHHVI), those with an acute SDH without a high-velocity impact injury (aSDHWO), and those with any combination of subacute or chronic blood products (mixed-SDH [mSDH]). Nine percent (n = 44) of patients experienced an aSDHHVI, 23% (n = 113) aSDHWO, and 68% (n = 337) mSDH. Between these groups, highly distinct patient populations were identified using several metrics for comparison. Most notably, aSDHHVI had a significantly worse neurological status at discharge (50% vs. 23% aSDHWO vs. 8% mSDH; p < 0.001) and mortality (25% vs. 8% aSDHWO vs. 4% mSDH; p < 0.001). Controlling for gender, midline shift (mm), and anticoagulation use in the acute SDH population, multivariable logistic regression revealed a 6.85x odds ratio (p < 0.001) for poor outcomes in those with a positive history for a high-velocity impact injury. As such, the distribution of patients that suffer an HVI related acute SDH versus those that do not can significantly affect the outcomes reported. Adoption of this stratification system will help address the heterogeneity of SDH reporting in the literature while still closely aligning with conventional reporting.
Back to a resilient future: Digital technologies for a sustainable supply chain
Authors: Winkelmann Stephanie , Guennoun Rajae , Möller Frederik , Schoormann Thorsten , van der Valk Hendrik
Published: May 2024

Economic, political, and societal pressure forces companies to act more sustainably. New legislation and regulation such as the Supply Chain Act, mandates companies to take responsibility for their actions as well as those of their supply chain collaborators. Meeting these requirements demands transparency. Digital technologies along the supply chain have the potential to collect diverse types of data and raise awareness for sustainability purposes. For example, data obtained from multiple supply chain participants can be used to estimate CO2 emissions or optimize resource utilization. Following guidelines for systematically reviewing a body of literature, this paper therefore investigates the distribution of digital technologies in supply chains for sustainability. Based on a collected corpus of 70 articles, we identify seven key digital technologies and indicate how they can be employed to contribute to economic, environmental, and social sustainability. The results show that (1) blockchain is the most used technology for sustainability within the supply chain and (2) the majority of articles on digital technologies in our corpus address the social dimension of sustainability. Our findings advance the understanding of how digitalization can transform supply chains into more sustainable entities and help practitioners decide which technology fits a certain sustainability dimension.
Nonlinear dynamics and game-theoretic modeling in economics and finance
Authors: Bischi Gian Italo , Baiardi Lorenzo Cerboni , Lamantia Fabio , Radi Davide
Published: May 2024

In this foreword to the Special Issue “Nonlinear dynamics and game-theoretical modeling in economics and finance” we review the contributions in the issue highlighting the economic results and the connections with aspects of dynamic analysis. Indeed, the common theme of the contributions is the focus on system dynamics and the latest analytical techniques. This issue is devoted to celebrating the 70th birthday of Professor Laura Gardini, who inspired a generation of scholars in the study of discrete-time systems and global methods of analysis.
Successful invasion: camera trap distance sampling reveals higher density for invasive raccoon dog compared to native mesopredators
Authors: Selonen V. , Brommer J. E. , Klangwald C. , Laaksonen T.
Published: May 2024

Monitoring population parameters of invasive species gains importance as these species continue to expand all over the world. Monitoring of invasive mammalian mesopredators is, however, complicated due to their nocturnal and secretive behaviour. In the European Union, the most common invasive mesopredator is the raccoon dog (Nyctereutes procyonoides), which causes concerns for native species, such as endangered waterfowl that may be subject to nest predation. We studied the density of mesopredators in southern Finland with wildlife cameras, using methodology of distance sampling. We deployed in total of 175 camera traps around 11 (spring 2020) and 16 (spring 2021) lakes or wetlands. We inferred densities for raccoon dogs, and for native mesopredators the red fox (Vulpes vulpes) and the European badger (Meles meles) for comparison. Raccoon dogs were found to have higher overall as well as site-specific densities (about 3.7 ind./km2) than badgers (1.2 ind./km2) and red foxes (0.6 ind./km2). The raccoon dogs also were present at every study wetland, while badgers were not found at all sites. The red fox showed more diurnal activity compared to raccoon dogs and badgers. Camera trap distance sampling enabled us to provide a density estimates on a rather small spatial and temporal scale for species of similar size and movement speed. It could therefore prove valuable as a long-term monitoring option, as climate trends are likely to further enable raccoon dog expansion. Currently this invasive species appears to be the most common mesopredator around wetlands in the southern boreal zone of southern Finland.
Do Old Board Directors Promote Corporate Social Responsibility?
Authors: Lee Han-Hsing , Liang Woan-lih , Tran Quynh-Nhu , Truong Quang-Thai
Published: May 2024

This study investigates the influence of old directors on corporate social responsibility (CSR) using roughly 25,000 firm-year observations from 2001 to 2015 in the United States. We employ the widely used selection, optimization, and compensation (SOC) model from psychology to explain the CSR decisions of old directors. Our results indicate that firms with a higher percentage of old directors tend to have lower engagement in CSR activities. To address endogeneity, we adopt the difference-in-differences method and use the event of sudden deaths and unexpected retirements of old directors and find that our results remain robust. Our analysis also reveals that the negative impact of old directors on CSR is more significant in firms where directors receive fewer reputational spillover benefits from CSR initiatives and/or firms exhibiting poor corporate governance. In addition, this adverse impact of old directors comes from two effects: a reduction in efforts to enhance CSR strengths and an increase in inaction to address CSR concerns. Overall, these findings suggest that the CSR decision-making process of old directors involves assessing the costs and benefits of CSR engagements, consistent with our hypothesis derived from the SOC model.
A review of machine learning methods used for educational data
Authors: Ersozlu Zara , Taheri Sona , Koch Inge
Published: May 2024

Integrating machine learning (ML) methods in educational research has the potential to greatly impact upon research, teaching, learning and assessment by enabling personalised learning, adaptive assessment and providing insights into student performance, progress and learning patterns. To reveal more about this notion, we investigated ML approaches used for educational data analysis in the last decade and provided recommendations for further research. Using a systematic literature review (SLR), we examined 77 publications from two large and high-impact databases for educational research using bibliometric mapping and evaluative review analysis. Our results suggest that the top five most frequently used keywords were similar in both databases. The majority of the publications (88%) utilised supervised ML approaches for predicting students’ performances and finding learning patterns. These methods include decision trees, support vector machines, random forests, and logistic regression. Semi-supervised learning methods were less frequently used, but also demonstrated promising results in predicting students’ performance. Finally, we discuss the implications of these results for statisticians, researchers, and policymakers in education.
Observational Assessment of Changes in Earth’s Energy Imbalance Since 2000
Authors: Loeb Norman G. , Ham Seung-Hee , Allan Richard P. , Thorsen Tyler J. , Meyssignac Benoit , Kato Seiji , Johnson Gregory C. , Lyman John M.
Published: May 2024

Satellite observations from the Clouds and the Earth’s Radiant Energy System show that Earth’s energy imbalance has doubled from 0.5 ± 0.2 Wm−2 during the first 10 years of this century to 1.0 ± 0.2 Wm−2 during the past decade. The increase is the result of a 0.9 ± 0.3 Wm−2 increase absorbed solar radiation (ASR) that is partially offset by a 0.4 ± 0.25 Wm−2 increase in outgoing longwave radiation (OLR). Despite marked differences in ASR and OLR trends during the hiatus (2000–2010), transition-to-El Niño (2010–2016) and post-El Niño (2016–2022) periods, trends in net top-of-atmosphere flux (NET) remain within 0.1 Wm−2 per decade of one another, implying a steady acceleration of climate warming. Northern and southern hemisphere trends in NET are consistent to 0.06 ± 0.31 Wm−2 per decade due to a compensation between weak ASR and OLR hemispheric trend differences of opposite sign. We find that large decreases in stratocumulus and middle clouds over the sub-tropics and decreases in low and middle clouds at mid-latitudes are the primary reasons for increasing ASR trends in the northern hemisphere (NH). These changes are especially large over the eastern and northern Pacific Ocean, and coincide with large increases in sea-surface temperature (SST). The decrease in cloud fraction and higher SSTs over the NH sub-tropics lead to a significant increase in OLR from cloud-free regions, which partially compensate for the NH ASR increase. Decreases in middle cloud reflection and a weaker reduction in low-cloud reflection account for the increase in ASR in the southern hemisphere, while OLR changes are weak. Changes in cloud cover in response to SST increases imply a feedback to climate change yet a contribution from radiative forcing or internal variability cannot be ruled out.
Counteroffers for faculty at research universities: who gets them, who doesn’t, and what factors produce them?
Authors: White-Lewis Damani K. , O’Meara KerryAnn , Mathews Kiernan , Havey Nicholas
Published: May 2024

In US higher education, faculty members may receive an outside offer of employment from an external organization, and then receive a corresponding counteroffer from their current institution. Counteroffers are written contracts made to individuals — either prematurely in anticipation of an outside offer, but most often after an outside offer — that outline improved salary, benefits, and/or other employment conditions with the hopes of retaining them. Though the norm of the “retention offer” is pervasive in the academy, in practice it can be much more nebulous, inefficient, discretionary, and inequitable. Few studies, however, empirically examine this process. In this study, we analyze quantitative institutional and survey data collected from 650 faculty by the Collaborative on Academic Careers in Higher Education (COACHE) to explore whether certain populations of faculty are more likely to receive counteroffers, and why. We found that women and racially minoritized scholars were less likely to receive counteroffers, and identified other factors that impact reception of counteroffers like faculty members’ desire to leave and their notification of leadership. We conclude by situating findings within extant research and offering implications for future research on counteroffers and their practice in faculty retention.
Bridges over troubled waters: Climate clubs, alliances, and partnerships as safeguards for effective international cooperation?
Authors: von Luepke Heiner , Neuhoff Karsten , Marchewitz Catherine
Published: May 2024

Driven by the motivation to raise the ambition level of climate action and to foster the transformation of economies, current climate policy discourse revolves around ways to improve cooperation between industrialized countries and emerging economies. We identify three broad types of initiatives—multilateral-cross sectoral, multilateral, sector specific, and climate and development partnerships—and assess them for potentials to deliver on such objectives with a specific focus on industry transformation. This paper provides new reflections on the institutionalization of international climate cooperation. Specifically, we demonstrate the urgent need to understand what values, norms, and underlying principles drive a cooperation in order to draw conclusions on how to best institutionalize climate cooperation rules.in-use. We conclude that an overemphasis on a CO2 price and on carbon border adjustment mechanisms, such as in the context of the initial proposals for a cross-sectoral climate club envisaged by G7 countries, would have contributed to a further polarization of the international landscape. We find, however, that multilateral, sectoral alliances play an important role for international goal setting and the convergence on standards, metrics, and benchmarks. Based on our analysis, we recommend strengthening multilateral, sector-specific partnerships. These can be focused on sectoral topics as a connector between countries, allowing for a strategically-aligned, increasingly deep collaboration. However, for any initiative to succeed, processes of international institutionalization will be needed in order to agree on rules for implementation based on aligned interests and equity. Building such institutions may well serve as a steppingstone toward more durable cooperation structures between developed economies and emerging economies. In sum, no existing cooperation approach is perfect, but three actions may be taken to move the agenda forward: First, reform of the carbon border adjustment mechanism and removing it from the center of climate club discussions, second, coupling sectoral alliances with climate and development partnerships, and three, designing them in a way to address fears of political influence seeking and superimposition of global north agendas on the global south.
On the algebraic connectivity of some token graphs
Authors: Dalfó C. , Fiol M. A.
Published: May 2024

The k-token graph $$F_k(G)$$

F
k

(
G
)

of a graph G is the graph whose vertices are the k-subsets of vertices from G, two of which are adjacent whenever their symmetric difference is a pair of adjacent vertices in G. It was proved that the algebraic connectivity of $$F_k(G)$$

F
k

(
G
)

equals the algebraic connectivity of G with a proof using random walks and interchange of processes on a weighted graph. However, no algebraic or combinatorial proof is known, and it would be a hit in the area. In this paper, we algebraically prove that the algebraic connectivity of $$F_k(G)$$

F
k

(
G
)

equals the one of G for new infinite families of graphs, such as trees, some graphs with hanging trees, and graphs with minimum degree large enough. Some examples of these families are the following: the cocktail party graph, the complement graph of a cycle, and the complete multipartite graph.
Development of a Self-Report Measure of Prediction in Daily Life: The Prediction-Related Experiences Questionnaire
Authors: O’Brien Amanda M. , May Toni A. , Koskey Kristin L. K. , Bungert Lindsay , Cardinaux Annie , Cannon Jonathan , Treves Isaac N. , D’Mello Anila M. , Joseph Robert M. , Li Cindy , Diamond Sidney , Gabrieli John D. E. , Sinha Pawan
Published: May 2024

Purpose

Predictions are complex, multisensory, and dynamic processes involving real-time adjustments based on environmental inputs. Disruptions to prediction abilities have been proposed to underlie characteristics associated with autism. While there is substantial empirical literature related to prediction, the field lacks a self-assessment measure of prediction skills related to daily tasks. Such a measure would be useful to better understand the nature of day-to-day prediction-related activities and characterize these abilities in individuals who struggle with prediction.

Methods

An interdisciplinary mixed-methods approach was utilized to develop and validate a self-report questionnaire of prediction skills for adults, the Prediction-Related Experiences Questionnaire (PRE-Q). Two rounds of online field testing were completed in samples of autistic and neurotypical (NT) adults. Qualitative feedback from a subset of these participants regarding question content and quality was integrated and Rasch modeling of the item responses was applied.

Results

The final PRE-Q includes 19 items across 3 domains (Sensory, Motor, Social), with evidence supporting the validity of the measure’s 4-point response categories, internal structure, and relationship to other outcome measures associated with prediction. Consistent with models of prediction challenges in autism, autistic participants indicated more prediction-related difficulties than the NT group.

Conclusions

This study provides evidence for the validity of a novel self-report questionnaire designed to measure the day-to-day prediction skills of autistic and non-autistic adults. Future research should focus on characterizing the relationship between the PRE-Q and lab-based measures of prediction, and understanding how the PRE-Q may be used to identify potential areas for clinical supports for individuals with prediction-related challenges.
Enhancing the O2 sensitivity of [Ru(bpy)3]2+ dye by incorporating SnO2 and Ni:SnO2
Authors: Oguzlar Sibel , Zeyrek Ongun Merve
Published: May 2024

Oxygen (O2)-sensitive probes encapsulated in a polymeric matrix have gas sensitivity improved by adding different metal oxide semiconductors (MOSs) to the composition. In this research, O2-sensitive tris(2,2′-bipyridyl) ruthenium(II) chloride ([Ru(bpy)3]Cl2) was chosen as a fluorophore, and SnO2 and Ni:SnO2 additives were used to enhance the oxygen sensitivity of the dye. While preparing sensing agents as a form of thin film and nanofiber, dye and MOSs powders were immobilized into the polymethylmethacrylate (PMMA) matrix in close proximity to each other. The oxygen-induced intensity measurements, decay time kinetics, and kinetic response were investigated for each of the sensing slides in the concentration range of 0–100% [O2]. Signal decreases in the emission-based intensity values of all MOSs-doped [Ru(bpy)3]2+-based complexes were monitored. Compared with free form, Ni:SnO2-doped [Ru(bpy)3]2+-based nanofiber agents exhibited a 4.03-fold increase in signal change (I0/I) ratio. The nanofiber structure, which allows the sensor slide to have a higher surface/volume ratio, allows O2 gas to penetrate more effectively. This can lead to greater interaction of the gas within the sensor matrix, resulting in more sensitive detection. Higher Stern Volmer (Ksv) values, greater O2 -induced sensing capabilities, more linear spectral measurements over larger concentration ranges, and faster response and recovery times show that MOSs-doped [Ru(bpy)3]2+-based sensing agents make promising candidates as oxygen probes.
Observing Interviewees’ Inner Self: How Authenticity Cues in Job Interviews Relate to Interview and Job Performance
Authors: Heimann Anna Luca , Schmitz-Wilhelmy Annika
Published: May 2024

Job interviews are among the most popular selection methods. Previous research suggests that interviewees who are perceived as being authentic are evaluated more favorably in job interviews. However, little is known about which behavioral cues elicit perceptions of authenticity in others and whether interviewees who exhibit such authenticity cues are more likely to perform better in the job interview and on their actual job. Drawing from person perception theories, the purpose of this study is to introduce the concept of authenticity cues to interview research and to examine the extent to which authenticity cues are related to (a) raters’ perceptions of interviewee authenticity, (b) interviewer ratings of interview performance, and (c) supervisor ratings of job performance. We used video recordings from 181 employed individuals participating in a mock interview to observe and rate interviewees’ authenticity cues. Results indicate that observers can distinguish between verbal and para/nonverbal authenticity cues and that both verbal and para/nonverbal cues influence the extent to which interviewees are perceived as authentic by independent raters. Moreover, we found that interviewees’ para/nonverbal authenticity cues were particularly relevant to predicting interview performance, whereas only verbal authenticity cues were related to job performance. In our analyses, we further considered the role of first impressions in the interview, interviewees’ verbal cognitive ability, and interviewees’ extraversion. Implications for theories of person perception, authenticity research, and interview practice are discussed.
Exact Solution to a Generalised Lillo–Mike–Farmer Model with Heterogeneous Order-Splitting Strategies
Authors: Sato Yuki , Kanazawa Kiyoshi
Published: May 2024

The Lillo–Mike–Farmer (LMF) model is an established econophysics model describing the order-splitting behaviour of institutional investors in financial markets. In the original article (Lillo et al. in Phys Rev E 71:066122, 2005), LMF assumed the homogeneity of the traders’ order-splitting strategy and derived a power-law asymptotic solution to the order-sign autocorrelation function (ACF) based on several heuristic reasonings. This report proposes a generalised LMF model by incorporating the heterogeneity of traders’ order-splitting behaviour that is exactly solved without heuristics. We find that the power-law exponent in the order-sign ACF is robust for arbitrary heterogeneous order-submission probability distributions. On the other hand, the prefactor in the ACF is very sensitive to heterogeneity in trading strategies and is shown to be systematically underestimated in the original homogeneous LMF model. Our work highlights that predicting the ACF prefactor is more challenging than the ACF exponent because many microscopic details (complex ingredients in actual data analyses) start to matter.
CoMadOut—a robust outlier detection algorithm based on CoMAD
Authors: Lohrer Andreas , Kazempour Daniyal , Hünemörder Maximilian , Kröger Peer
Published: May 2024

Unsupervised learning methods are well established in the area of anomaly detection and achieve state of the art performances on outlier datasets. Outliers play a significant role, since they bear the potential to distort the predictions of a machine learning algorithm on a given dataset. Especially among PCA-based methods, outliers have an additional destructive potential regarding the result: they may not only distort the orientation and translation of the principal components, they also make it more complicated to detect outliers. To address this problem, we propose the robust outlier detection algorithm CoMadOut, which satisfies two required properties: (1) being robust towards outliers and (2) detecting them. Our CoMadOut outlier detection variants using comedian PCA define, dependent on its variant, an inlier region with a robust noise margin by measures of in-distribution (variant CMO) and optimized scores by measures of out-of-distribution (variants CMO*), e.g. kurtosis-weighting by CMO+k. These measures allow distribution based outlier scoring for each principal component, and thus, an appropriate alignment of the degree of outlierness between normal and abnormal instances. Experiments comparing CoMadOut with traditional, deep and other comparable robust outlier detection methods showed that the performance of the introduced CoMadOut approach is competitive to well established methods related to average precision (AP), area under the precision recall curve (AUPRC) and area under the receiver operating characteristic (AUROC) curve. In summary our approach can be seen as a robust alternative for outlier detection tasks.
A Parallel Model for Jointly Extracting Entities and Relations
Authors: Chen Zuqin , Zheng Yujie , Ge Jike , Yu Wencheng , Wang Zining
Published: May 2024

Extracting relational triples from a piece of text is an essential task in knowledge graph construction. However, most existing methods either identify entities before predicting their relations, or detect relations before recognizing associated entities. This order may lead to error accumulation because once there is an error in the initial step, it will accumulate to subsequent steps. To solve this problem, we propose a parallel model for jointly extracting entities and relations, called PRE-Span, which consists of two mutually independent submodules. Specifically, candidate entities and relations are first generated by enumerating token sequences in sentences. Then, two independent submodules (Entity Extraction Module and Relation Detection Module) are designed to predict entities and relations. Finally, the predicted results of the two submodules are analyzed to select entities and relations, which are jointly decoded to obtain relational triples. The advantage of this method is that all triples can be extracted in just one step. Extensive experiments on the WebNLG*, NYT*, NYT and WebNLG datasets show that our model outperforms other baselines at 94.4%, 88.3%, 86.5% and 83.0%, respectively.
Negative conspecific plant-soil feedback on alien plants co-growing with natives is partly mitigated by another alien
Authors: Chen Duo , van Kleunen Mark
Published: May 2024

Background and aims

Naturalized alien and native plants can impact each other directly when they grow next to each other, but also indirectly through their soil legacies. These alien-native interactions can also be modified by the presence of a third alien or native species. However, it is unknown how the performance of co-growing alien and native species is affected by their soil legacies and by the presence of an additional species.

Methods

In our two-phase plant-soil-feedback experiment, soils were first conditioned by eight herbaceous species, four of which are naturalized and four of which are native to Germany. We then grew all 16 pairwise alien-native species combinations on soil conditioned by the respective alien or native species, on a mixture of soils conditioned by both species or on control soil. Each pair of test plants was grown on these soils without or with an additional alien or native species.

Results

Soil conditioning, and particularly conspecific soil conditioning, reduced growth of the alien and native test plants. The addition of another species also reduced growth of the test plants. However, the negative conspecific soil-legacy effect on alien test plants was reduced when the additional species was also alien.

Conclusion

The negative conspecific plant-soil feedback for alien and native plants in our study could promote their coexistence. However, as partial alleviation of negative conspecific effects on alien plants occurred with an additional alien species, the chances of coexistence of alien and native species might decrease when there are multiple alien species present.
Q methodologist views on the future of Q: a
study of a research community
Authors: Ramlo Susan
Published: May 2024

It has been almost 90 years since William Stephenson’s 1935
letter to Nature that opened the door for Q methodology [Q]. Criticisms and
excitement ensued and continue into the present within and outside of the Q research
community. Yet, any research community contains researchers with different
positionalities about the methodology’s philosophical framework, and best
practices regarding data collection and/or data analysis. A relatively recent Q
study indicated differences of opinion among Q methodologists when it comes to data
analysis and its philosophical framework. Twenty years ago, Hurd and Brown uncovered
four divergent viewpoints about the Q community’s view of the future of Q.
Thus, especially with Q’s growing popularity, it seemed time to repeat that
study with some change to the subjective statements used within the data collection
phase, as many changes have occurred especially regarding technological advances for
data collection and data analysis. Two viewpoints were uncovered, Tradition and Community, with a focus on the
theoretical framework provided by Stephenson and the welcoming nature of the Q
community, and Unorthodox with Expansion of Q,
with a yearning to expand Q both physically and theoretically including a
willingness to move beyond Stephenson’s vision. The discussion and conclusion
focus on the implications of these perspectives and their shared consensus for the
future of Q methodology as well as implications for other research methodologies. In
other words, this study provides a demonstration of complementarity for
understanding the behavior of all types of research communities.
The Precarity of Progress: Implications of a Shifting Gendered Division of Labor for Relationships and Well-Being as a Function of Country-Level Gender Equality
Authors: Fisher Alexandra N. , Ryan Michelle K. , Liao Yuan-Hsi , Mikołajczak Gosia , Riedijk Larisa , Leander N. Pontus , Abakoumkin Georgios , Abdul Khaiyom Jamilah Hanum , Ahmedi Vjollca , Agostini Maximilian , Atta Moshin , Bagci Sabahat Cigdem , J. Bélanger Jocelyn , Berisha Kida Edona , B. I. Bernardo Allan , Chobthamkit Phatthanakit , Choi Hoon-Seok , Cristea Mioara , Damnjanovic Kaja , Danyliuk Ivan , Di Santo Daniela , M. Douglas Karen , Enea Violeta , J. Fitzsimons Gavan , Gómez Ángel , Gützkow Ben , Hamaidia Ali , Helmy Mai , Hudiyana Joevarian , Jovanović Veljko , Jovanović Veljko , Kende Anna , Keng Shian-Ling , Kieu Tra Thi Thanh , Koc Yasin , Kreienkamp Jannis , Kurapov Anton , Lantos Nóra Anna , P. Lemay Edward , Lueders Adrian , Malik Najma Iqbal , O. McCabe Kira , Mehulić Jasmina , Molinario Erica , Moyano Manuel , Muhammad Hayat , Muluk Hamdi , F. Nisa Claudia , Nyúl Boglárka , A. O’Keefe Paul , Olivias Osuna Jose Javier , Osin Evgeny , Park Joonha , Pica Gennaro , Pierro Antonio , Rees Jonas , Reitsema Anne Margit , Rullo Marika , Samekin Adil , M. Schumpe Birga , A. Selim Heyla , Stanton Michael Vicente , Tseliou Eleftheria , R vanDellen Michelle , Vázquez Alexandra , Wollast Robin , Yeung Victoria Wai-Lan , Zand Somayeh , Žeželj Iris Lav , Zúñiga Claudia
Published: May 2024

The onset of the COVID-19 pandemic saw a shift toward a more traditional division of labor–one where women took greater responsibility for household tasks and childcare than men. We tested whether this regressive shift was more acutely perceived and experienced by women in countries with greater gender equality. Cross-cultural longitudinal survey data for women and men (N = 10,238) was collected weekly during the first few months of the pandemic. Multilevel modelling analyses, based on seven waves of data collection, indicated that a regressive shift was broadly perceived but not uniformly felt. Women and men alike perceived a shift toward a more traditional division of household labor during the first few weeks of the pandemic. However, this perception only undermined women’s satisfaction with their personal relationships and subjective mental health if they lived in countries with higher levels of economic gender equality. Among women in countries with lower levels of economic gender equality, the perceived shift predicted higher relationship satisfaction and mental health. There were no such effects among men. Taken together, our results suggest that subjective perceptions of disempowerment, and the gender role norms that underpin them, should be considered when examining the gendered impact of global crisis.
Development of a Battery for the Measurement of Financial Capabilities in Young People
Authors: León William Fernando Duran , Chaparro Olga Lucia Manrique , Rojas Camilo Andrés Ramírez
Published: May 2024

Measuring financial capabilities among young people poses a challenge for scholars. In this study, we developed a set of ten scales to assess various behaviors, attitudes, and knowledge, allowing for a comprehensive examination of the construct. We designed a pool of items and invited 746 participants, aged 16 to 29, who were divided into two groups for studying the psychometric properties of the tests. The first group underwent an Exploratory Factor Analysis, while the second group underwent a Confirmatory Factor Analysis. Through these analyses, we identified five dimensions of financial behaviors, four dimensions of financial attitudes, and one dimension of knowledge or financial literacy. The scales were combined to measure two financial capabilities: Financial Saving Capability and Responsible Debt Management Capability. Furthermore, we identified distinct profiles of young people associated with each proposed financial capability. Finally, we offer a conceptual discussion of the financial capabilities construct, present scales with reliable and valid measurements, and propose avenues for future research.
3D-MuPPET: 3D Multi-Pigeon Pose Estimation and Tracking
Authors: Waldmann Urs , Chan Alex Hoi Hang , Naik Hemal , Nagy Máté , Couzin Iain D. , Deussen Oliver , Goldluecke Bastian , Kano Fumihiro
Published: May 2024

Markerless methods for animal posture tracking have been rapidly developing recently, but frameworks and benchmarks for tracking large animal groups in 3D are still lacking. To overcome this gap in the literature, we present 3D-MuPPET, a framework to estimate and track 3D poses of up to 10 pigeons at interactive speed using multiple camera views. We train a pose estimator to infer 2D keypoints and bounding boxes of multiple pigeons, then triangulate the keypoints to 3D. For identity matching of individuals in all views, we first dynamically match 2D detections to global identities in the first frame, then use a 2D tracker to maintain IDs across views in subsequent frames. We achieve comparable accuracy to a state of the art 3D pose estimator in terms of median error and Percentage of Correct Keypoints. Additionally, we benchmark the inference speed of 3D-MuPPET, with up to 9.45 fps in 2D and 1.89 fps in 3D, and perform quantitative tracking evaluation, which yields encouraging results. Finally, we showcase two novel applications for 3D-MuPPET. First, we train a model with data of single pigeons and achieve comparable results in 2D and 3D posture estimation for up to 5 pigeons. Second, we show that 3D-MuPPET also works in outdoors without additional annotations from natural environments. Both use cases simplify the domain shift to new species and environments, largely reducing annotation effort needed for 3D posture tracking. To the best of our knowledge we are the first to present a framework for 2D/3D animal posture and trajectory tracking that works in both indoor and outdoor environments for up to 10 individuals. We hope that the framework can open up new opportunities in studying animal collective behaviour and encourages further developments in 3D multi-animal posture tracking.