julilili42/papers huggingface dataset:
The impact of text topic and assumed human vs. AI authorship on competence and quality assessment
2024-05-31

Background While Large Language Models (LLMs) are considered positively with respect to technological progress and abilities, people are rather opposed to machines making moral decisions. But the circumstances under which algorithm aversion or algorithm appreciation are more likely to occur with respect to LLMs have not yet been sufficiently investigated. Therefore, the aim of this study was to investigate how texts with moral or technological topics, allegedly written either by a human author or by ChatGPT, are perceived. Methods In a randomized controlled experiment, n = 164 participants read six texts, three of which had a moral and three a technological topic (predictor text topic). The alleged author of each text was randomly either labeled “ChatGPT” or “human author” (predictor authorship). We captured three dependent variables: assessment of author competence, assessment of content quality, and participants' intention to submit the text in a hypothetical university course (sharing intention). We hypothesized interaction effects, that is, we expected ChatGPT to score lower than alleged human authors for moral topics and higher than alleged human authors for technological topics and vice versa. Results We only found a small interaction effect for perceived author competence, p = 0.004, d = 0.40, but not for the other dependent variables. However, ChatGPT was consistently devalued compared to alleged human authors across all dependent variables: there were main effects of authorship for assessment of the author competence, p &amp;lt; 0.001, d = 0.95; for assessment of content quality, p &amp;lt; 0.001, d = 0.39; as well as for sharing intention, p &amp;lt; 0.001, d = 0.57. There was also a small main effect of text topic on the assessment of text quality, p = 0.002, d = 0.35. Conclusion These results are more in line with previous findings on algorithm aversion than with algorithm appreciation. We discuss the implications of these findings for the acceptance of the use of LLMs for text composition.
Thinking disposition education improves cognitive reflection: Experimental results from an intervention study
2024-05-31

Cognitive reflection is a construct measuring one's ability to disengage automatic or type I processing and instead activate effortful deliberation, described as type II processing in dual process theories. Successfully overriding intuitive responses is posited to rely on, in part, trait-like attributes known as thinking dispositions, though a causal link has not been established. The present research is the first randomized controlled trial investigating the effect of a novel thinking disposition intervention (TDI)—a 7-week educational curriculum—on cognitive reflection performance. In the present study, subjects (N = 338) were randomized to either the TDI or a control condition. A Bayesian modeling approach suggests positive and moderate effects. Moreover, those in the treatment were over twice as likely to make CRT gains than those in the control group. Additional mediation and moderation analyses were conducted to test whether the TDI impacts CRT via thinking dispositions such as need for cognition and intellectual humility, and/or whether such attributes meaningfully interact with the intervention. Thinking dispositions do not appear to mediate this relationship, neither do they moderate the effect of the intervention. Implications for dual process theory are discussed.
Using Gaze Transition Entropy to Detect Classroom Discourse in a Virtual Reality Classroom
2024-05-31

This paper explores gaze entropy as a metric for detecting classroom discourse events in a virtual reality (VR) classroom. Using data from a laboratory experiment with N = 240 secondary school students, we distinguished between events of teacher-centered classroom discourse (question, hand raising, answer) and teacher explanation by analyzing their transition and stationary gaze entropy. Employing multi-level regression models, both entropy measures effectively discriminated between the two events and distinguished different levels of classroom participation as indicated by the degree of hand-raising by virtual students. Furthermore, using both measures in a logistic regression model, the potential of gaze entropy could be demonstrated by predicting the two events with 67% accuracy. By analyzing transition and stationary entropy, the study attempts to uncover different gaze patterns associated with learning events in a virtual classroom. The results contribute to the research and development of VR scenarios that help to simulate effective learning environments.
A new legacy: potential of zooarchaeology by mass spectrometry in the analysis of North American megafaunal remains
2024-05-31

Museum legacy collections, often derived from large-scale archaeological excavations, can serve as paleoenvironmental archives of Late Pleistocene megafaunal composition and dynamics. Many of these collections, however, contain large quantities of highly fragmented and morphologically indistinct bones that cannot be identified to a specific taxon and are therefore of limited use to paleoenvironmental and archaeological analyses. Here, we explore the potential of Zooarchaeology by Mass Spectrometry (ZooMS) to identify fossil bone fragments and complement morphological identifications in legacy collections housed at the Smithsonian’s National Museum of Natural History. To undertake this work, we collected fragmented bone specimens of Late Pleistocene megafauna from six archaeological sites in Colorado that are currently housed in the Department of Anthropology, and then performed pilot ZooMS screening. Our analysis successfully retrieved taxonomic information from 80% of the analyzed material, highlighting the potential of future ZooMS studies on museum collections to investigate human-megafaunal interactions in late Pleistocene North America.
Zero Shot Learning in Pupil Detection
2024-05-31

In eye tracking, pupil detection is a crucial step for gaze estimation. While there are a plethora of datasets with accurate annotations, new devices, such as differently placed cameras, usually require more data to be annotated since the new perspective is not part of the datasets so far. The research community has already published multiple simple simulators for data generation, as well as rendering-based approaches for the human eye. We created a dataset with different camera perspectives along with different challenges and evaluated the pupil simulators as well as the rendering-based approaches for zero-shot pupil detection. In our evaluation, we highlight the limitations of the simulators and the rendering-based approaches in terms of the different challenges.
An Eyelid Simulator for Zero Shot Eyelid Segmentation
2024-05-31

Eyelid detection is an important feature for fatigue estimation in autonomous driving, for example. It allows for the estimation of driver readiness if a takeover event occurs, and is therefore crucial for the safety of car passengers and traffic participants. We propose to use two splines and two randomly filled regions as a simple eyelid simulator for deep neural network training. This allows a fast generation of perfectly labeled training images and only needs a fraction of computational resources if compared to rendering-based approaches. We compared our approach against the training on real-world images as well as other rendering-based approaches in terms of accuracy and resource consumption. In addition, we evaluated different combinations of the rendering-based approaches, real-world images, and our approach.
Gaze-based Assessment of Expertise in Chess
2024-05-31

Chess is known worldwide and has acquired a deep cultural significance. It is recognized as a sport by the International Olympic Committee, and this sport has around 600 million players worldwide. Since chess is a strategic game, it requires an estimate of the future actions of the opposite player and the integration of these estimates into the own planning. This makes it a perfect sport to study expertise classification based on eye tracking data, since the players sit still and only have visual information about the actions of the opposite player. We conducted a small study and investigated different features to estimate the outcome of a chess game. The level of expertise of the players was determined by the number of years they had played chess already. We found, that transfer learning seems to be a promising approach since it can be trained on larger amounts of data without annotations.
Tripartite quantum Rabi model with trapped Rydberg ions
2024-05-31

We investigate a tripartite quantum Rabi model (TQRM) wherein a bosonic mode concurrently couples to two spin-<a:math xmlns:a="http://www.w3.org/1998/Math/MathML"><a:mrow><a:mn>1</a:mn><a:mo>/</a:mo><a:mn>2</a:mn></a:mrow></a:math> particles through a spin-spin interaction, resulting in a spin-spin-boson coupling—a departure from conventional quantum Rabi models featuring bipartite spin-boson couplings. The symmetries of the TQRM depend on the detuning parameter, representing the energy difference between the spin states. At zero detuning a parity symmetry renders the TQRM reducible to a quantum Rabi model. A subradiant-to-superradiant transition in the ground state is predicted as the tripartite coupling strength increases. For nonzero detuning the total spin emerges as the sole conserved quantity in the TQRM. It is found that superradiance prevails in the ground state as long as the tripartite coupling remains nonzero. We derive the Braak <b:math xmlns:b="http://www.w3.org/1998/Math/MathML"><b:mi mathvariant="script">G</b:mi></b:math> function of the TQRM analytically, with which the eigenspectra are obtained. The TQRM can be realized in a viable trapped Rydberg ion quantum simulator, where the required tripartite couplings and single-body interactions in the TQRM are naturally present. Our study opens opportunities to explore and create correlations and entanglement in the spin and motional degrees of freedoms with the TQRM. Published by the American Physical Society 2024
Communication breakdown: Gaze-based prediction of system error for AI-assisted robotic arm simulated in VR
2024-05-31

Neurological degenerative conditions can affect motor functions, making mobility daunting. Recent configurations of mobility devices that leverage artificial intelligence (AI) show its ability to handle complex information like user input. We create a virtual reality environment to measure participants' reactions to correct and incorrect feedback from an AI-assistance system. Using gaze to evaluate these reactions, we investigate whether we can automatically predict an upcoming system error. Our results show that gaze reactions occur within 300 ms when the system highlights user input, but the delay extends to 1 second without highlighting. Subject dependent gaze behavior proved complicated for developing a generalizable model based on previous work using TCNs for online recognition of upcoming errors. Therefore, more adaptable models for individuals may be a better alternative for gaze-based accessibility systems.
Using mobile eye tracking for gaze- and head-contingent vision simulations
2024-05-31

Eye tracking enables the implementation of gaze-contingent visual impairment simulations, holding promise for research, clinical uses, and demonstrations. While head-mounted displays (HMDs) are common for such simulations, screen-based implementations can be an alternative for individuals who are reluctant or unable to use HMDs. Screen-based simulations are less likely to induce virtual reality sickness and allow eye contact and social interaction with the demonstrator or examiner. To improve the immersion, we use mobile eye tracking with fiducial markers for a head- and gaze-contingent simulation of visual impairments on a screen.
An Evaluation of Gaze-Based Person Identification with Different Stimuli
2024-05-31

In eye tracking, the most promising approaches for person identification are based on the iris. Therefore, the iris of a subject is extracted and compared against a database of stored iris templates or directly classified by a deep neural network. While this approach is robust and has found its way into many practical applications like security access devices, it has some limitations, since it is possible to fake the iris. This can be done either by presenting a rendered image or by using a contact lens. Our research focuses on the gaze behavior of a subject for person identification. Therefore, we present different stimuli as well as moving dots. In past research, only a static dot has been used so far. We show that, especially, the combination of different stimuli is a promising approach and could be used as an additional security layer in combination with iris recognition.
Assessment of body-related attention processes via mobile eye tracking: A pilot study to validate an automated analysis pipeline
2024-05-31

Body dissatisfaction and eating disorder symptoms have previously been linked to biased attentional processes when looking at one's own body. The tendency is to focus on body parts self-defined to be most unattractive, compared to those self-defined to be most attractive. This attention bias is assumed to contribute to the maintenance of body dissatisfaction. Therefore, there is a need to measure and analyze attentional bias efficiently in studies on etiology and treatment of body dissatisfaction and eating disorders. We validate an automated analysis pipeline for mobile eye-tracking data while looking at one's own body in a large mirror. The pipeline uses and extends a machine-learning based body pose estimation algorithm by segmenting identified body parts into subregions defined by provided texture coordinates. Results of a pilot study include a guided-viewing validation task, in which participants were asked to look at specific body regions, and a 3-minute free-viewing task.
Fluid Intelligence and Mental Effort during Block Programming: What the Eyes Can Tell Us
2024-05-31

Programming skills are becoming increasingly important in our digital age. Here, block-based programming languages offer a great way for novices to learn programming, as their drag-and-drop mechanic makes the assembly of code very intuitive. In this study we wanted to answer the question whether fluid intelligence helps with learning to program and what influence it has on the amount of effort needed to succeed in block-programming tasks. We used eye tracking to look into physiological measures of mental effort, focusing on pupil diameter, fixation characteristics, and blinks. Our results suggest that the mental effort needed to successfully complete block-programming tasks is not linked to fluid intelligence and all learners have to invest similar amounts of effort in order to succeed. Additionally, we found that high fluid intelligence speeds up the completion of basic block-programming tasks, but does not influence the time it takes to solve more complex block-programming tasks.
Eye tracking data set of academics making an omelette: An egg-breaking work
2024-05-31

Just as there are numerous ways to cook an egg, there are numerous ways to recreate a YouTube video of cooking an omelette. We created a dataset of 10 academics replicating a viral video of making an omelette. We evaluated the saccade behavior during the varying subtasks and found differences related to the actions (whisking, sprinkling, etc.) and the objects (eggs, butter, plate, etc.). This dataset can further offer insight into eye movements in complex tasks and is potentially even applicable for task planning and intention prediction. The available data can be found at https://zenodo.org/doi/10.5281/zenodo.10875267.
Modulation of dorsal premotor cortex disrupts neuroplasticity of primary motor cortex in young and older adults
2024-05-31

Previous transcranial magnetic stimulation (TMS) research suggests that dorsal premotor cortex (PMd) influences neuroplasticity within primary motor cortex (M1) through indirect (I) wave interneuronal circuits. However, it is unclear how the influence of PMd on the plasticity of M1 I-waves changes with advancing age. This study therefore investigated the neuroplastic effects of intermittent theta burst stimulation (iTBS) to M1 early and late I-wave circuits when preceded by iTBS (PMd iTBS-M1 iTBS) or sham stimulation (PMd sham-M1 iTBS) to PMd in 15 young and 16 older adults. M1 excitability was assessed with motor evoked potentials (MEP) recorded from right first dorsal interosseous using posterior-anterior (PA) and anterior-posterior (AP) current TMS at standard stimulation intensities (PA1mV, AP1mV) and reduced stimulation intensities (PA0.5mV, early I-waves; AP0.5mV, late I-waves). PMd iTBS-M1 iTBS disrupted the expected facilitation of PA0.5mV (to M1 iTBS) in young and older adults (P = 0.009), whereas the intervention had no effect on AP0.5mV facilitation in either group (P = 0.305). This suggests that the influence of PMd on M1 plasticity is preserved in older adults and may involve projections to early I-wave circuits within M1.
Characterization of complete responders to nivolumab + gemcitabine-cisplatin vs gemcitabine-cisplatin alone and patients with lymph node–only metastatic urothelial carcinoma from the CheckMate 901 trial.
2024-06-01

4509 Background: In the CheckMate 901 trial, combination nivolumab (NIVO) + gemcitabine-cisplatin (GC) demonstrated significant improvements in overall survival (OS) and progression-free survival (PFS) with compelling objective response rates (ORR; 57.6% with NIVO+GC vs 43.1% with GC alone) and deep, durable complete responses (CR; 21.7% with NIVO+GC vs 11.8% with GC alone) in patients (pts) with previously untreated unresectable or metastatic urothelial carcinoma (mUC). Lymph node (LN)-only metastatic disease is a favorable prognostic factor in pts with mUC and a subset of pts achieve durable disease-free, treatment-free survival with GC +/- surgical consolidation. We conducted a post hoc analysis to characterize the subset of pts with CR, with further analysis of pts with LN-only mUC. Methods: In the global, open-label, randomized, phase 3 CheckMate 901 (NCT03036098) trial, cisplatin-eligible pts received NIVO 360 mg + GC every 3 wk for ≤6 cycles followed by NIVO 480 mg every 4 wk until disease progression/unacceptable toxicity or up to a maximum of 2 yrs, or GC every 3 wk for ≤6 cycles. Primary endpoints were OS and PFS by blinded independent central review (BICR). ORR per BICR and safety were exploratory endpoints. These post hoc analyses evaluated treatment outcomes in complete responders and in pts with LN-only disease. Results: Of the 608 pts randomized, 102 (16.8%) achieved a CR. Baseline disease characteristics of these pts are shown in the Table. As pts with LN-only mUC were enriched in the CR group, additional analysis of this subgroup was performed. Of all randomized pts, 54 treated with NIVO+GC and 56 treated with GC had LN-only mUC. In these pts, the ORR and CR rate was 81.5% (95% CI 68.6-90.7) and 63.0% versus 64.3% (50.4-76.6%) and 33.9% for NIVO+GC and GC, respectively. Median OS (95% CI) in LN-only pts was 46.3 (24.0-NE) mos with NIVO+GC vs 24.9 (21.4-29.9) with GC (HR, 0.58, 95% CI 0.34-1.00), and median PFS (95% CI) was 30.5 (9.6-NE) mos with NIVO+GC vs 8.8 (7.5-10.9) mos with GC (HR 0.38, 95% CI 0.22-0.66). Conclusions: NIVO+GC generated deep responses in CheckMate 901 with a fixed duration of chemotherapy and up to 2 years NIVO. Exploratory characterization of pts with CR identified a group of pts enriched with LN-only disease.In pts with LN-only mUC, NIVO+GC induced durable disease control and clinically meaningful improvements in OS and PFS vs GC alone. These results provide additional support for NIVO plus cisplatin-based chemo as a first-line treatment option for pts with mUC. Clinical trial information: NCT03036098 . [Table: see text]
Fifteen Years of Integrated Terrestrial Environmental Observatories (TERENO) in Germany: Functions, Services, and Lessons Learned
2024-06-01

Abstract The need to develop and provide integrated observation systems to better understand and manage global and regional environmental change is one of the major challenges facing Earth system science today. In 2008, the German Helmholtz Association took up this challenge and launched the German research infrastructure TERrestrial ENvironmental Observatories (TERENO). The aim of TERENO is the establishment and maintenance of a network of observatories as a basis for an interdisciplinary and long‐term research program to investigate the effects of global environmental change on terrestrial ecosystems and their socio‐economic consequences. State‐of‐the‐art methods from the field of environmental monitoring, geophysics, remote sensing, and modeling are used to record and analyze states and fluxes in different environmental disciplines from groundwater through the vadose zone, surface water, and biosphere, up to the lower atmosphere. Over the past 15 years we have collectively gained experience in operating a long‐term observing network, thereby overcoming unexpected operational and institutional challenges, exceeding expectations, and facilitating new research. Today, the TERENO network is a key pillar for environmental modeling and forecasting in Germany, an information hub for practitioners and policy stakeholders in agriculture, forestry, and water management at regional to national levels, a nucleus for international collaboration, academic training and scientific outreach, an important anchor for large‐scale experiments, and a trigger for methodological innovation and technological progress. This article describes TERENO's key services and functions, presents the main lessons learned from this 15‐year effort, and emphasizes the need to continue long‐term integrated environmental monitoring programmes in the future.
Blindly separated spontaneous network-level oscillations predict corticospinal excitability
2024-06-01

Abstract Objective. The corticospinal responses of the motor network to transcranial magnetic stimulation (TMS) are highly variable. While often regarded as noise, this variability provides a way of probing dynamic brain states related to excitability. We aimed to uncover spontaneously occurring cortical states that alter corticospinal excitability. Approach. Electroencephalography (EEG) recorded during TMS registers fast neural dynamics—unfortunately, at the cost of anatomical precision. We employed analytic Common Spatial Patterns technique to derive excitability-related cortical activity from pre-TMS EEG signals while overcoming spatial specificity issues. Main results. High corticospinal excitability was predicted by alpha-band activity, localized adjacent to the stimulated left motor cortex, and suggesting a travelling wave-like phenomenon towards frontal regions. Low excitability was predicted by alpha-band activity localized in the medial parietal–occipital and frontal cortical regions. Significance. We established a data-driven approach for uncovering network-level neural activity that modulates TMS effects. It requires no prior anatomical assumptions, while being physiologically interpretable, and can be employed in both exploratory investigation and brain state-dependent stimulation.