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Online polarization research currently focuses on studying single-issue opinion distributions or computing distance metrics of interaction network structures. Limited data availability often restricts studies to positive interaction data, which can misrepresent the reality of a discussion. We introduce a novel framework that aims at combining these three aspects, content and interactions, as well as their nature (positive or negative), while challenging the prevailing notion of polarization as an umbrella term for all forms of online conflict or opposing opinions. In our approach, built on the concepts of cleavage structures and structural balance of signed social networks, we factorize polarization into two distinct metrics: Antagonism and Alignment. Antagonism quantifies hostility in online discussions, based on the reactions of users to content. Alignment uses signed structural information encoded in long-term user-user relations on the platform to describe how well user interactions fit the global and/or traditional sides of discussion. We can analyse the change of these metrics through time, localizing both relevant trends but also sudden changes that can be mapped to specific contexts or events. We apply our methods to two distinct platforms: Birdwatch, a US crowd-based fact-checking extension of Twitter, and DerStandard, an Austrian online newspaper with discussion forums. In these two use cases, we find that our framework is capable of describing the global status of the groups of users (identification of cleavages) while also providing relevant findings on specific issues or in specific time frames. Furthermore, we show that our four metrics describe distinct phenomena, emphasizing their independent consideration for unpacking polarization complexities.

ImportanceIndividuals who are amyloid-positive with subjective cognitive decline and clinical features increasing the likelihood of preclinical Alzheimer disease (SCD+) are at higher risk of developing dementia. Some individuals with SCD+ undergo amyloid-positron emission tomography (PET) as part of research studies and frequently wish to know their amyloid status; however, the disclosure of a positive amyloid-PET result might have psychological risks.ObjectiveTo assess the psychological outcomes of the amyloid-PET result disclosure in individuals with SCD+ and explore which variables are associated with a safer disclosure in individuals who are amyloid positive.Design, Setting, and ParticipantsThis prospective, multicenter study was conducted as part of The Amyloid Imaging to Prevent Alzheimer Disease Diagnostic and Patient Management Study (AMYPAD-DPMS) (recruitment period: from April 2018 to October 2020). The setting was 5 European memory clinics, and participants included patients with SCD+ who underwent amyloid-PET. Statistical analysis was performed from July to October 2022.ExposuresDisclosure of amyloid-PET result.Main Outcomes and MeasuresPsychological outcomes were defined as (1) disclosure related distress, assessed using the Impact of Event Scale–Revised (IES-R; scores of at least 33 indicate probable presence of posttraumatic stress disorder [PTSD]); and (2) anxiety and depression, assessed using the Hospital Anxiety and Depression scale (HADS; scores of at least 15 indicate probable presence of severe mood disorder symptoms).ResultsAfter disclosure, 27 patients with amyloid-positive SCD+ (median [IQR] age, 70 [66-74] years; gender: 14 men [52%]; median [IQR] education: 15 [13 to 17] years, median [IQR] Mini-Mental State Examination [MMSE] score, 29 [28 to 30]) had higher median (IQR) IES-R total score (10 [2 to 14] vs 0 [0 to 2]; P P P P P = .06) and Depression (–1.0 [–2.0 to 0.0] vs –1.0 [–3.0 to 0.0]; P = .46) deltas (score after disclosure – scores at baseline). In patients with amyloid-positive SCD+, despite the small sample size, higher education was associated with lower disclosure-related distress (ρ = –0.43; P = .02) whereas the presence of study partner was associated with higher disclosure-related distress (W = 7.5; P = .03). No participants with amyloid-positive SCD+ showed probable presence of PTSD or severe anxiety or depression symptoms at follow-up.Conclusions and RelevanceThe disclosure of a positive amyloid-PET result to patients with SCD+ was associated with a bigger psychological change, yet such change did not reach the threshold for clinical concern.

Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.

Impediment to local anesthetic solution in the epidural space results in unsatisfactory pain relief during labor epidural. Patients with a history of back trauma and spinal instrumentation have increased rates of epidural failure due to patchy spread of local anesthetic with obliterated epidural space. Dual Epidural Catheters (DEC) can be used in such clinical scenarios with complete labor analgesia and improved patient satisfaction. We present the successful management of a parturient with vertebral fracture at risk for epidural failure and neurologic injury due to bone fragments and inserted cranial and caudal to the fractured vertebra using ultrasound to avoid neurologic sequelae.

The overturning streamfunction is a widely used metric to monitor ocean circulation changes in the North Atlantic Ocean. Analogously, it is known that an overturning circulation develops in the Mediterranean Sea, although substantially weaker and smaller than in the Atlantic. In this work we use monthly mean fields from a high-resolution ocean reanalysis (1/16◦ × 1/16◦) to explore seasonal and interannual variability of Mediterranean Sea overturning circulation in depth and water mass parameter spaces (potential density, potential temperature, salinity) from 1987 to 2018 (both included). Results show a clear single zonal clockwise transport cell in all three spaces that extends from the Strait of Gibraltar to the Levantine Basin, in which water masses tend to densify as they move eastward. This densification is mainly controlled by salinity in the Eastern Mediterranean basin (EMED), while in the Western Mediterranean (WMED) both salinity and potential temperature variations should be taken into account. In contrast, the meridional overturning transport, much more complex, is able to better capture smaller-scale variations since it responds faster to perturbations in the circulation. Seasonal variations in overturning transport are reflected in the size and strength of overturning cells in all spaces, being cells remarkably narrower in winter than in summer. Regarding interannual changes, we show that the meridional overturning transport in density space is significantly correlated with the North Atlantic Oscillation, the Mediterranean Oscillation Index and the Scandinavian pattern during wintertime in the WMED, and with the Eastern Atlantic and the East Atlantic-Western Russian in the EMED. The overturning metric in density space captures well the Eastern Mediterranean Transient, that occurred during years 1992–1996. Finally, we explore the usefulness of overturning metric to detect and track water mass changes associated to shorter scale events, using as example the strong deep convection events of years 2004–2006 in the Gulf of Lion, which marked the beginning of the Western Mediterranean Transition. J.-M. Sayol thanks the financial support by Generalitat Valenciana and the European Social Fund (ESF) through the APOSTD/2020/254 grant. Part of this research was performed during his visit to IMEDEA (UIB-CSIC), also funded by the APOSTD/2020/254 grant. D. García-García and I. Vigo are partially funded by Spanish Ministry of Science, Innovation and Universities grant number PID2021-122142OB-I00, and Generalitat Valenciana grant numbers PROMETEO/2021/030 and GVA-THINKINAZUL/2021/035.

The wealth of text data generated by social media has enabled new kinds of analysis of emotions with language models. These models are often trained on small and costly datasets of text annotations produced by readers who guess the emotions expressed by others in social media posts. This affects the quality of emotion identification methods due to training data size limitations and noise in the production of labels used in model development. We present LEIA, a model for emotion identification in text that has been trained on a dataset of more than 6 million posts with self-annotated emotion labels for happiness, affection, sadness, anger, and fear. LEIA is based on a word masking method that enhances the learning of emotion words during model pre-training. LEIA achieves macro-F1 values of approximately 73 on three in-domain test datasets, outperforming other supervised and unsupervised methods in a strong benchmark that shows that LEIA generalizes across posts, users, and time periods. We further perform an out-of-domain evaluation on five different datasets of social media and other sources, showing LEIA's robust performance across media, data collection methods, and annotation schemes. Our results show that LEIA generalizes its classification of anger, happiness, and sadness beyond the domain it was trained on. LEIA can be applied in future research to provide better identification of emotions in text from the perspective of the writer. The models produced for this article are publicly available at https://huggingface.co/LEIA

Lumped parameter methods aim to simplify the evolution of spatially-extended or continuous physical systems to that of a "lumped" element representative of the physical scales of the modeled system. For systems where the definition of a lumped element or its associated physics may be unknown, modeling tasks may be restricted to full-fidelity simulations of the physics of a system. In this work, we consider data-driven modeling tasks with limited point-wise measurements of otherwise continuous systems. We build upon the notion of the Universal Differential Equation (UDE) to construct data-driven models for reducing dynamics to that of a lumped parameter and inferring its properties. The flexibility of UDEs allow for composing various known physical priors suitable for application-specific modeling tasks, including lumped parameter methods. The motivating example for this work is the plunge and dwell stages for friction-stir welding; specifically, (i) mapping power input into the tool to a point-measurement of temperature and (ii) using this learned mapping for process control.

Emotions play a crucial role in information processing. Prior studies indicate that high-arousal emotions may elicit rapid, intuitive thinking, tricking people into judging misinformation as truthful. Yet, few studies have distinguished prior affective state from emotional reactions to false news, both of which may influence belief in falsehoods in different ways. Replicating and extending Martel et al. (2020), we conducted a pre-registered online survey in Austria (N = 422), investigating associations of emotions and discernment of false and real news related to COVID-19. We found no associations of affective state with discernment, but different emotional responses to false and real news — namely, more anger and less joy for false news. A curvilinear relationship of anger with discernment showed that both participants who were good and bad at discerning real from false news responded with anger. The automated analysis of 5,613 open-ended textual responses suggested that anger may have arisen for different reasons in these different groups. It seemed to also arise when people recognized the false news as such, not only when people accepted it. We conclude that studies need to distinguish between prior affective state and emotional response to misinformation and consider individuals’ prior beliefs as determinants of emotions.

How can citizens moderate hate, toxicity, and extremism in online discourse? We analyze a large corpus of more than 130,000 discussions on German Twitter over the turbulent four years marked by the migrant crisis and political upheavals. With a help of human annotators, language models, machine learning classifiers, and longitudinal statistical analyses, we discern the dynamics of different dimensions of discourse. We find that expressing simple opinions, not necessarily supported by facts but also without insults, relates to the least hate, toxicity, and extremity of speech and speakers in subsequent discussions. Sarcasm also helps in achieving those outcomes, in particular in the presence of organized extreme groups. More constructive comments such as providing facts or exposing contradictions can backfire and attract more extremity. Mentioning either outgroups or ingroups is typically related to a deterioration of discourse in the long run. A pronounced emotional tone, either negative such as anger or fear, or positive such as enthusiasm and pride, also leads to worse outcomes. Going beyond one-shot analyses on smaller samples of discourse, our findings have implications for the successful management of online commons through collective civic moderation.

Within the setting of the AdS/CFT correspondence, we ask about the power of computers in the presence of gravity. We show that there are computations on $n$ qubits which cannot be implemented inside of black holes with entropy less than $O(2^n)$. To establish our claim, we argue computations happening inside the black hole must be implementable in a programmable quantum processor, so long as the inputs and description of the unitary to be run are not too large. We then prove a bound on quantum processors which shows many unitaries cannot be implemented inside the black hole, and further show some of these have short descriptions and act on small systems. These unitaries with short descriptions must be computationally forbidden from happening inside the black hole.

Supplemental material, sj-docx-1-jmh-10.1177_15579883231153018 for Differences in Metabolomic Profiles by Birthplace in Mexican-Origin Hispanic Men Who Participated in a Weight Loss Lifestyle Intervention by Melissa Lopez-Pentecost, David O. Garcia, Xiaoxiao Sun, Cynthia A. Thomson, H.-H. Sherry Chow and Jessica A. Martinez in American Journal of Men’s Health

Supplemental material, sj-docx-1-jmh-10.1177_15579883231153018 for Differences in Metabolomic Profiles by Birthplace in Mexican-Origin Hispanic Men Who Participated in a Weight Loss Lifestyle Intervention by Melissa Lopez-Pentecost, David O. Garcia, Xiaoxiao Sun, Cynthia A. Thomson, H.-H. Sherry Chow and Jessica A. Martinez in American Journal of Men’s Health

Calyx dimensions and distances do not differ between different host-symbiont combinations. Five calices from 25 colonies containing Cladocopium latusorum and 75 with Durusdinium glynnii were selected for morphometric analysis. a) Neither the maximum or minimum diameters differed between the two combinations (p=0.094 and p=0.052, respectively), b) nor did the average distance to the nearest calyx (p=0.78).

Contains fulltext : 290155.pdf (Publisher’s version ) (Closed access)

Zeitschrift für Hochschulentwicklung, Zeitschrift für Hochschulentwicklung (Journal for Higher Education Development), This article presents a progress report from the last two years of the Teaching Digital Thinking (TDT) project. This project aims to implement new concepts, didactic methods, and teaching formats for sustainable digital transformation in Austrian Universities’ curricula by introducing new digital competencies. By equipping students and teachers with 21st-century digital competencies, partner universities can contribute to solving global challenges and organizing pilot projects. In line with the overall project aims, this article presents the ongoing digital transformation activities, courses, and research in the project, which have been carried out by the five partner universities since 2020, and briefly discusses the results. This article presents a summary of the research and educational activities carried out within two parts: complementary research and pilot projects., Dieser Beitrag präsentiert die Fortschritte des Projekts Teaching Digital Thinking (TDT) der letzten zwei Jahre. Das Projekt zielt darauf ab, neue Konzepte, didaktische Methoden und Lehrformate für eine nachhaltige digitale Transformation in die Curricula der österreichischen Universitäten zu implementieren, indem neue digitale Kompetenzen verankert werden. Durch die Vermittlung von digitalen Kompetenzen für das 21. Jahrhundert an Studierende und Lehrende können die Partneruniversitäten einen Beitrag zur Lösung globaler Herausforderungen leisten. In Übereinstimmung mit den übergeordneten Projektzielen werden in diesem Beitrag die laufenden Aktivitäten, Lehrveranstaltungen und Forschungsarbeiten zur digitalen Transformation, die von den fünf Partneruniversitäten seit 2020 durchgeführt werden, vorgestellt und die Ergebnisse kurz diskutiert.

Heat waves are causing declines in coral reefs globally. Coral thermal responses depend on multiple, interacting drivers, such as past thermal exposure, endosymbiont community composition, and host genotype. This makes the understanding of their relative roles in adaptive and/or plastic responses crucial for anticipating impacts of future warming. Here, we extracted DNA and RNA from 102 Pocillopora colonies collected from 32 sites on 11 islands across the Pacific Ocean to characterize host-photosymbiont fidelity and to investigate patterns of gene expression across a historical thermal gradient. We report high host-photosymbiont fidelity and show that coral and microalgal gene expression respond to different drivers. Differences in photosymbiotic association had only weak impacts on host gene expression, which was more strongly correlated with the historical thermal environment, whereas, photosymbiont gene expression was largely determined by microalgal lineage. Overall, our results reveal a three-tiered strategy of thermal acclimatization in Pocillopora underpinned by host-photosymbiont specificity, host transcriptomic plasticity, and differential photosymbiotic association under extreme warming. published

Published in : IFAC-PapersOnLine 55(10):1363-1368. doi :10.1016/j.ifacol.2022.09.580; International audience; This study addresses disassembly lot-sizing that determines the ordering and disassembly schedules of end-of-life (EOL) products and subassemblies to satisfy items demands. A stochastic version with uncertain ordering lead time (OLT) is considered for the first time. Here, OLT represents the time elapsed between placing an order and receiving it (only an EOL product can be ordered). Stochastic integer programming model is developed for the objective of minimizing the expected sum of setup, purchase, inventory and backlog costs. To test the performance of the proposed model, computational experiments were done on various test instances and are reported. The results show that the performance of the proposed model depends on the size of the ordering lead times, the number of periods and components.

Previous work conducted by Laura Vuillier and Rui Sun (Vuillier, L., et al, 2018) found that participants' diversity of emoji usage on Facebook (aggregated at the country level) was related to country-level wellbeing. Here we would like to test whether this pattern is found at the individual level. Specifically, we predict that individuals' emoji usage diversity on Twitter is positively related to their subjective wellbeing. We would like to use data collected by Laura Vuillier, Rui Sun, and colleagues in 2016-2017 to examine this question. In this dataset, participants reported their Twitter ID, as well as completing questionnaires measuring their personality, wellbeing, etc. The Twitter IDs will be used to collect their publicly available tweets, process their text and extract users' emoji, and Shannon's Index will be used to calculate the emoji diversity for each participant. Citation: Vuillier, L., Brooks, A. W., … & Norton, M. I. (2018). Amount and diversity of digital emotional expression predicts happiness. Harvard Business School.

esophageal anastomosis dehiscence is a serious complication after esophageal cancer surgery with high mortality risk. One of the treatment options is self-expanding esophageal prostheses. Our aim was to evaluate the outcome of esophageal prostheses in the management of suture dehiscences after oncologic surgery.we performed a descriptive and retrospective study with patients diagnosed with esophageal anastomosis fistula or dehiscence treated by esophageal prosthesis between the years 2015 and 2021. We considered technical success as the correct positioning of the prosthesis with visualization of anastomotic leak closure after release of the prosthesis during endoscopy, and clinical success the resolution of dehiscence after removal of the prosthesis 8 weeks after positioning.technical success was 95% and clinical success 89%.in our center, esophageal prostheses are a treatment option for fistulas and anastomotic dehiscence after surgery with a high success rate and few complications.

Wikipedia is a community-created encyclopedia that contains information about notable people from different countries, epochs and disciplines and aims to document the world's knowledge from a neutral point of view. However, the narrow diversity of the Wikipedia editor community has the potential to introduce systemic biases such as gender biases into the content of Wikipedia. In this paper we aim to tackle a sub problem of this larger challenge by presenting and applying a computational method for assessing gender bias on Wikipedia along multiple dimensions. We find that while women on Wikipedia are covered and featured well in many Wikipedia language editions, the way women are portrayed starkly differs from the way men are portrayed. We hope our work contributes to increasing awareness about gender biases online, and in particular to raising attention to the different levels in which gender biases can manifest themselves on the web., in The International AAAI Conference on Web and Social Media (ICWSM2015), Oxford, May 2015

Full reproduction materials for the manuscript entitled "Social media discourse of political elites: An asymmetric American exceptionalism".

One topic that repeatedly sparks debates in politics and the society is “gender-neutral language”. For instance, in languages such as German, French, or Hindi, plural forms of job occupations and societal roles are often in a generic-masculine form instead of a gender-neutral form. Although meant as “generic”, this generic-masculine form excludes women from everyday language and might even entail the cognitive effect that listeners and readers will less likely think of women. Several studies have demonstrated this and related cognitive effects in the past. Due to the societal relevance of gender-neutral language, we propose a direct replication and extension of a classic German study by Stahlberg, Sczesny, and Braun (2001, Experiment 2; https://doi.org/10.1177/0261927X01020004004) in a multi-lab setting.

CSS Lab Holiday Paper Series 2020

The spread of online misinformation is increasingly perceived as a problem for societal cohesion and democracy. Much attention has focused on the role of social media as a vector of misinformation. The role of political leaders has attracted less research attention, even though leaders demonstrably influence media coverage and public opinion, and even though politicians who "speak their mind" are perceived by segments of the public as authentic and honest even if their statements are unsupported by evidence or facts. Here we show that in the last decade, U.S. politicians' conception of truth has undergone a distinct shift, with authentic but evidence-free belief-speaking becoming more prominent and more differentiated from evidence-based truth seeking. We analyze communications by members of the U.S. Congress on Twitter between 2011 and 2022 and show that political speech has fractured into two distinct components related to belief-speaking and evidence-based truth-seeking, respectively, and that belief-speaking, but not truth-seeking, can be associated with the sharing of untrustworthy information. We show that in tweets by conservative members of Congress, an increase in belief-speaking of 10% is associated with a decrease of 13.7 points of quality (using the NewsGuard scoring system) in the sources shared in a tweet. In addition, we find that an increase of belief-speaking language by 10% in the shared articles themselves is associated with a drop in NewsGuard score of 7.9 points for members of both parties. By contrast, increase in truth-seeking language in tweets and articles is associated with an increase in quality of sources. The results support the hypothesis that the current dissemination of misinformation in political discourse is in part driven by a new understanding of truth and honesty that has replaced reliance on evidence with the invocation of subjective belief.

A major question surrounding L and T type dwarfs is the evolution of their atmospheric structures on rotational timescales. Multiwavelength photometry allows us to probe different depths of the atmosphere and the different cloud layers that reside there. Simultaneous multiwavelength observations allow us to investigate further intricacies, such as differential rotation. Here, we present the results of near - simultaneous JKs multi-band photometry of SIMP0136, a known variable T2.5 dwarf. The observations were taken using the Perkins Telescope in Flagstaff, Arizona, USA and the data was reduced using the PINES Analysis Toolkit. The PINES Analysis Toolkit is a pipeline specifically written to deal with the systematics of Mimir, the infrared detector on the Perkins Telescope, while also optimizing reduction techniques for faint variable objects. As this project grows and additional objects are observed, we will complete a full investigation into the color modulation along the L/T transition region to attempt to determine the physical mechanisms affecting the evolution of atmospheric structure., {"references":["Gagné, J. et al. (2017), ApJ, 841L, 1G","Tamburo, P. et al. (2022), AJ, 163, 253T","Lew, B. W. P. et al. (2020), AJ, 159, 125L"]}

The sustained interest in laser-driven neutron sources comes from their compactness and affordability while opening the possibilities for a wide range of applications, potentially complementing the research carried out at large-scale spallation facilities. An experiment was carried out at the Vulcan Petawatt facility (CLF, UK) to generate bright, ultra-short neutron bursts employing cryogenic ribbons of solid deuterium. Cryogenic targets can in principle produce single species, debris-free ion beams suitable for a wide range of applications. Deuterium ions up to 25 MeV/nucleon were detected in the forward direction, correspondingly with high energy neutrons in high fluxes being produced. Due to the low density of the target (∼200 mg/cc) and the significant radiation pressure at the delivered laser intensities (5 × 1019 − 5 × 1020 W/cm2), considerable compression of the deuterium plasma at the front surface is expected and accelerating bulk deuterium by the hole-boring mechanism. The neutrons are subsequently produced by the d(d,n)3He fusion reaction in the target bulk driven by ions produced by the hole-boring front. Preliminary particle-in-cell simulations support the experimental results to explain the underlying physics involving ps-class lasers at linear polarisation.

Laser powder bed fusion is a promising technology for local deposition and microstructure control, but it suffers from defects such as delamination and porosity due to the lack of understanding of melt pool dynamics. To study the fundamental behavior of the melt pool, both geometric and thermal sensing with high spatial and temporal resolutions are necessary. This work applies and integrates three advanced sensing technologies: synchrotron X-ray imaging, high-speed IR camera, and high-spatial-resolution IR camera to characterize the evolution of the melt pool shape, keyhole, vapor plume, and thermal evolution in Ti-6Al-4V and 410 stainless steel spot melt cases. Aside from presenting the sensing capability, this paper develops an effective algorithm for high-speed X-ray imaging data to identify melt pool geometries accurately. Preprocessing methods are also implemented for the IR data to estimate the emissivity value and extrapolate the saturated pixels. Quantifications on boundary velocities, melt pool dimensions, thermal gradients, and cooling rates are performed, enabling future comprehensive melt pool dynamics and microstructure analysis. The study discovers a strong correlation between the thermal and X-ray data, demonstrating the feasibility of using relatively cheap IR cameras to predict features that currently can only be captured using costly synchrotron X-ray imaging. Such correlation can be used for future thermal-based melt pool control and model validation. Office of Naval Research [N00014-18-1-2794] Published version Research reported in this publication was supported by the Office of Naval Research under Award Number N00014-18-1-2794. We would like to thank Alex Deriy from APS for assisting with the beamline experiments; Thomas Feldhausen from Oak Ridge National Lab for preparing the SS-410 samples; Scott Lancaster and Randall Waldron from Virginia Tech for assisting with the high-spatial IR fixture fabrication.

Because of its willingness to share data with academia and industry, Twitter has been the primary social media platform for scientific research as well as for consulting businesses and governments in the last decade. In recent years, a series of publications have studied and criticized Twitter's APIs and Twitter has partially adapted its existing data streams. The newest Twitter API for Academic Research allows to "access Twitter's real-time and historical public data with additional features and functionality that support collecting more precise, complete, and unbiased datasets." The main new feature of this API is the possibility of accessing the full archive of all historic Tweets. In this article, we will take a closer look at the Academic API and will try to answer two questions. First, are the datasets collected with the Academic API complete? Secondly, since Twitter's Academic API delivers historic Tweets as represented on Twitter at the time of data collection, we need to understand how much data is lost over time due to Tweet and account removal from the platform. Our work shows evidence that Twitter's Academic API can indeed create (almost) complete samples of Twitter data based on a wide variety of search terms. We also provide evidence that Twitter's data endpoint v2 delivers better samples than the previously used endpoint v1.1. Furthermore, collecting Tweets with the Academic API at the time of studying a phenomenon rather than creating local archives of stored Tweets, allows for a straightforward way of following Twitter's developer agreement. Finally, we will also discuss technical artifacts and implications of the Academic API. We hope that our work can add another layer of understanding of Twitter data collections leading to more reliable studies of human behavior via social media data.

Envelope thermal transmittance strongly influences building energy consumption, so there is a significant interest in using methods that assess it accurately. The quantitative infrared thermography method is among the most studied methods to assess thermal transmittance as this method could be used to analyse building envelopes qualitatively and quantitatively. However, its main limitation is the great variety of approaches. Their greater differences are the convective heat transfer coefficient and the place from which the measurement is carried out. This chapter comparatively analyses the experimental results obtained in previous studies. The analysis showed that the approaches from the interior using expressions of adimensional numbers allow accurate characterizations of thermal transmittance to be obtained.

Supplemental material, sj-pdf-4-jcb-10.1177_0271678X221078616 for Assessment of motion and model bias on the detection of dopamine response to behavioral challenge by Michael A Levine, Joseph B Mandeville, Finnegan Calabro, David Izquierdo-Garcia, Daniel B Chonde, Kevin T Chen, Inki Hong, Julie C Price, Beatriz Luna and Ciprian Catana in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-6-jcb-10.1177_0271678X221078616 for Assessment of motion and model bias on the detection of dopamine response to behavioral challenge by Michael A Levine, Joseph B Mandeville, Finnegan Calabro, David Izquierdo-Garcia, Daniel B Chonde, Kevin T Chen, Inki Hong, Julie C Price, Beatriz Luna and Ciprian Catana in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-7-jcb-10.1177_0271678X221078616 for Assessment of motion and model bias on the detection of dopamine response to behavioral challenge by Michael A Levine, Joseph B Mandeville, Finnegan Calabro, David Izquierdo-Garcia, Daniel B Chonde, Kevin T Chen, Inki Hong, Julie C Price, Beatriz Luna and Ciprian Catana in Journal of Cerebral Blood Flow & Metabolism

Additional file 1.

Supplemental material, sj-pdf-1-jcb-10.1177_0271678X221078616 for Assessment of motion and model bias on the detection of dopamine response to behavioral challenge by Michael A Levine, Joseph B Mandeville, Finnegan Calabro, David Izquierdo-Garcia, Daniel B Chonde, Kevin T Chen, Inki Hong, Julie C Price, Beatriz Luna and Ciprian Catana in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-6-jcb-10.1177_0271678X221078616 for Assessment of motion and model bias on the detection of dopamine response to behavioral challenge by Michael A Levine, Joseph B Mandeville, Finnegan Calabro, David Izquierdo-Garcia, Daniel B Chonde, Kevin T Chen, Inki Hong, Julie C Price, Beatriz Luna and Ciprian Catana in Journal of Cerebral Blood Flow & Metabolism

Increased sharing of untrustworthy information on social media platforms is one of the main challenges of our modern information society. Because information disseminated by political elites is known to shape citizen and media discourse, it is particularly important to examine the quality of information shared by politicians. Here we show that from 2016 onward, members of the Republican party in the U.S. Congress have been increasingly sharing links to untrustworthy sources. The proportion of untrustworthy information posted by Republicans versus Democrats is diverging at an accelerating rate, and this divergence has worsened since president Biden was elected. This divergence between parties seems to be unique to the U.S. as it cannot be observed in other western democracies such as Germany and the United Kingdom, where left-right disparities are smaller and have remained largely constant.

Supplemental material, sj-pdf-5-jcb-10.1177_0271678X221078616 for Assessment of motion and model bias on the detection of dopamine response to behavioral challenge by Michael A Levine, Joseph B Mandeville, Finnegan Calabro, David Izquierdo-Garcia, Daniel B Chonde, Kevin T Chen, Inki Hong, Julie C Price, Beatriz Luna and Ciprian Catana in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-2-jcb-10.1177_0271678X221078616 for Assessment of motion and model bias on the detection of dopamine response to behavioral challenge by Michael A Levine, Joseph B Mandeville, Finnegan Calabro, David Izquierdo-Garcia, Daniel B Chonde, Kevin T Chen, Inki Hong, Julie C Price, Beatriz Luna and Ciprian Catana in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-7-jcb-10.1177_0271678X221078616 for Assessment of motion and model bias on the detection of dopamine response to behavioral challenge by Michael A Levine, Joseph B Mandeville, Finnegan Calabro, David Izquierdo-Garcia, Daniel B Chonde, Kevin T Chen, Inki Hong, Julie C Price, Beatriz Luna and Ciprian Catana in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-2-jcb-10.1177_0271678X221078616 for Assessment of motion and model bias on the detection of dopamine response to behavioral challenge by Michael A Levine, Joseph B Mandeville, Finnegan Calabro, David Izquierdo-Garcia, Daniel B Chonde, Kevin T Chen, Inki Hong, Julie C Price, Beatriz Luna and Ciprian Catana in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-3-jcb-10.1177_0271678X221078616 for Assessment of motion and model bias on the detection of dopamine response to behavioral challenge by Michael A Levine, Joseph B Mandeville, Finnegan Calabro, David Izquierdo-Garcia, Daniel B Chonde, Kevin T Chen, Inki Hong, Julie C Price, Beatriz Luna and Ciprian Catana in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-docx-1-anp-10.1177_00048674221126649 for Association of 7 million+ tweets featuring suicide-related content with daily calls to the Suicide Prevention Lifeline and with suicides, United States, 2016–2018 by Thomas Niederkrotenthaler, Ulrich S Tran, Hubert Baginski, Mark Sinyor, Markus J Strauss, Steven A Sumner, Martin Voracek, Benedikt Till, Sean Murphy, Frances Gonzalez, Madelyn Gould, David Garcia, John Draper and Hannah Metzler in Australian & New Zealand Journal of Psychiatry

Supplemental material, sj-pdf-1-jcb-10.1177_0271678X221078616 for Assessment of motion and model bias on the detection of dopamine response to behavioral challenge by Michael A Levine, Joseph B Mandeville, Finnegan Calabro, David Izquierdo-Garcia, Daniel B Chonde, Kevin T Chen, Inki Hong, Julie C Price, Beatriz Luna and Ciprian Catana in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-3-jcb-10.1177_0271678X221078616 for Assessment of motion and model bias on the detection of dopamine response to behavioral challenge by Michael A Levine, Joseph B Mandeville, Finnegan Calabro, David Izquierdo-Garcia, Daniel B Chonde, Kevin T Chen, Inki Hong, Julie C Price, Beatriz Luna and Ciprian Catana in Journal of Cerebral Blood Flow & Metabolism