ethicalabs/Research-Intent-Collab huggingface dataset:
What long-period comets tell us about the Oort Cloud

Context. The Oort Cloud is located in the farthest outskirts of the Solar System, extending to a heliocentric distance of several tens of thousands of au, and remains the last region of the Solar System where no object has been detected. Thus, all our knowledge of the Oort Cloud has been deduced from the observed long-period comets that are thought to originate from it. Aims. We aimed to retrieve valuable information that might be hidden in the orbital distributions of the observed long-period comets. Such information will allow us to impose constraints not only on the present shape of the Oort Cloud but also on its initial shape 4.5 Gyr ago. This has direct implications for the scenario proposed for its formation. Methods. We used two different databases of long-period comets. First, we calculated the distribution of orbital elements that might carry valuable information about the shape of the Oort Cloud. Then, we compared the distribution with that obtained from two synthetic samples of observable comets. These samples correspond to two considerably different initial configurations: one is a disk model, where we consider a swarm of comets with orbits aligned to the ecliptic plane and with a cometary perihelion close to the giant planets. The other is an isotropic model, where we consider a fully isotropic and thermalized initial distribution of comets. Results. The comparison revealed that the databases contained several features that were in better agreement with the disk model than with the isotropic model. The Oort Cloud contained an initial disk of objects with perihelia close to the planetary region of the Solar System and aphelia extending out to roughly 20 000 au. Some parts of this disk likely remain in the present Solar System. However, the fit to the disk model is poor. The discrepancy between the observational and synthetic results indicates that some dynamical processes in the current Oort Cloud were not included in either model. Conclusions. This initial shape of the Oort Cloud implies that planetary scattering was crucial during its formation. In addition, the fact that some dynamical features are still detec table 4.5 Gyr after the cloud formation imposes constraints on the role of exosolar effects, such as giant molecular clouds, Galactic tides, and the stellar cluster surrounding the Solar System at the time of its formation.
The right to a healthy environment,a social environmental justice approach

The right to a healthy environment gained recognition in many constitutions around the globe. Such legal recognition has been regarded as transformative in terms of better environmental regulations. To understand how this right has been realized by citizens through their national courts, from the social environmental justice perspective is the aim of this thesis. The implications of the exercise of this right on the role of the Executive will likewise be examined. The thesis adopts the case study method to ascertain how national courts in selected jurisdictions interpreted the constitutional right to a healthy environment. In almost all the cases examined, the national courts exemplified a judicial activism in giving meaning and vision for the enforcement of the right. The judicial authorities properly delineated the constitutional duty of the other branches of the government to fulfill the right to a healthy environment. The philosophy behind the national courts' rulings reflected and applied notions of social environmental justice, in a way that merited the claimants' plea to live in a healthy environment. In this sense, the rulings encapsulated the vision of social environmental justice that social justice and environmental justice are mutually supportive and integral to serving the ends of justice in an environmental context.
Schmitt, Michael N. (ed.). Tallinn Manual on the International Law Applicable to Cyber Warfare. Cambridge: Cambridge University Press, 2013, xix, 282 s. ISBN 9781107024434.

Schmitt, Michael N. (ed.). Tallinn Manual on the International Law Applicable to Cyber Warfare. Cambridge: Cambridge University Press, 2013, xix, 282 s. ISBN 9781107024434.
DESIGN AND EXPERIMENTAL OPTIMIZATION OF A CONTINUOUS VIBRATION-BASED LYCIUM BARBARUM L. HARVESTING DEVICE

Compared with manual harvesting of Lycium barbarum, existing large-scale harvesters have achieved a certain degree of efficiency improvement. Nevertheless, their intermittent operation mode remains a bottleneck restricting overall harvesting performance. To address this issue, a continuous vibration-based L. barbarum harvesting device was developed in this study. Plackett–Burman experiments indicated that vibration angle, vibration frequency, and the spacing between the upper and lower vibrating rods were the primary factors affecting the harvesting performance. Further parameter optimization experiments were carried out by considering the harvesting rate of ripe fruits, the mis-harvesting rate of unripe fruits, and the damage rate of ripe fruits. The optimal parameter combination was determined as a vibration angle of 46°, a vibration frequency of 9 Hz, and a spacing of 62 mm between the upper and lower vibrating rods. Based on these parameters, performance verification tests were conducted. The results showed that the harvesting rate of ripe fruits reached 85.40%, the mis-harvesting rate of unripe fruits was 4.61%, and the damage rate of ripe fruits was 3.19%. These findings provide technical and equipment support for the development of continuous mechanized harvesting of L. barbarum.
An annotated human blastocyst dataset to benchmark deep learning architectures for in vitro fertilization

AbstractMedical Assisted Reproduction proved its efficacy to treat the vast majority forms of infertility. One of the key procedures in this treatment is the selection and transfer of the embryo with the highest developmental potential. To assess this potential, clinical embryologists routinely work with static images (morphological assessment) or short video sequences (time-lapse annotation). Recently, Artificial Intelligence models were utilized to support the embryo selection procedure. Even though they have proven their great potential in different in vitro fertilization settings, there is still considerable room for improvement. To support the advancement of algorithms in this research field, we built a dataset consisting of static blastocyst images and additional annotations. As such, Gardner criteria annotations, depicting a morphological blastocyst rating scheme, and collected clinical parameters are provided. The presented dataset is intended to be used to train deep learning models on static morphological images to predict Gardner’s criteria and clinical outcomes such as live birth. A benchmark of human expert’s performance in annotating Gardner criteria is provided.
Employees’ Unethical Prosocial Organizational Behavior as an Outcome of Managers’ Democratic, Autocratic, and Laissez-Faire Leadership Styles: A Study on the Turkish Tourism Sector

This study examines the relationships democratic, autocratic, and laissez-faire leadership styles have onunethical prosocial organizational behaviors (UPB). The research is designed in accordance with the causal-comparative method. Affective commitment is defined in the research model as the mediating variable with normativecommitment, continuous commitment, and performance bonus as the moderating variables. The research data havebeen collected from hotel employees (n = 362) who are directly in contact with customers. The analyses have beenperformed using SmartPLS 3.9. According to the results, no relationships have been found for democratic, autocratic, and laissez-faire leadership styles with UPB. The mediating variable of affective commitment has been found tohave no significant effect on the relationship between leadership styles and UPB. The independent variable of normative commitment has been found to be positively correlated with UPB at a significance level of p < 0.05. However,it was not found to have any moderating effect as a moderating variable on the relationship between leadershipstyles and UPB. No significant relationship has been found for continuance commitment either as an independentvariable or as a moderating variable. Meanwhile, performance bonus, which is another mediating variable, has beenfound to generate a significant difference at the level of p = .000 between employees who receive bonuses and thosewho do not in terms of the relationship between normative commitment and UPB.
Clinical trial methodology to assess the efficacy/effectiveness of long-acting antipsychotics: Randomized controlled trials vs naturalistic studies

Schizophrenia presents unique difficulties in clinical trial design associated with the condition's variable presentation and clinical course, and multiple features influencing affect, cognition, volition and perception. Randomized controlled trials (RCTs) are explanatory studies using a carefully selected patient population, predefined assessment intervals and, generally, symptom-focused endpoints. Naturalistic studies are pragmatic, with no active intervention, and outcomes that are generally those used in clinical practice (e.g. hospitalization, relapse rate). Both naturalistic studies and RCTs have pros and cons, making it difficult for physicians in clinical practice to apply research findings to their own treatment decisions. The choice of clinical trial design can have a significant impact on the comparative effectiveness or efficacy of drugs. This is particularly true for studies comparing long-acting injectable (LAI) antipsychotics with oral antipsychotics in schizophrenia, in which RCTs generally show no benefit for LAIs over oral drugs, whereas observational studies do. The more pragmatic the study design, the more likely it is to show a benefit for LAIs versus oral therapy. This article reviews the pros and cons of different study types, using published examples. Criteria are outlined to help physicians design appropriate prospective studies in schizophrenia including the relevant pragmatic and/or explanatory features, as required.
Impact of detector simulation in particle physics collider experiments

Through the last three decades, accurate simulation of the interactions of particles with matter and modeling of detector geometries has proven to be of critical importance to the success of the international high-energy physics (HEP) experimental programs. For example, the detailed detector modeling and accurate physics of the Geant4-based simulation software of the CMS and ATLAS particle physics experiments at the European Center of Nuclear Research (CERN) Large Hadron Collider (LHC) was a determinant factor for these collaborations to deliver physics results of outstanding quality faster than any hadron collider experiment ever before. This review article highlights the impact of detector simulation on particle physics collider experiments. It presents numerous examples of the use of simulation, from detector design and optimization, through software and computing development and testing, to cases where the use of simulation samples made a difference in the precision of the physics results and publication turnaround, from data-taking to submission. It also presents estimates of the cost and economic impact of simulation in the CMS experiment. Future experiments will collect orders of magnitude more data with increasingly complex detectors, taxing heavily the performance of simulation and reconstruction software. Consequently, exploring solutions to speed up simulation and reconstruction software to satisfy the growing demand of computing resources in a time of flat budgets is a matter that deserves immediate attention. The article ends with a short discussion on the potential solutions that are being considered, based on leveraging core count growth in multicore machines, using new generation coprocessors, and re-engineering HEP code for concurrency and parallel computing.
Digital Phenotyping in Pediatric Mental Health: From Passive Sensing to Precision Psychiatry—A Narrative Review

The escalating crisis in pediatric mental health has rendered traditional, episodic care models insufficient. Reliance on infrequent clinical interviews often fails to capture the rapid, non-linear fluctuations of adolescent psychiatric disorders, leaving clinicians blind to prodromal signs of relapse. This narrative review synthesizes emerging evidence from 2020 to 2026 regarding digital phenotyping—the continuous, passive collection of behavioral data via smartphone sensors—as a paradigm shift toward precision psychiatry. We examine how raw sensor inputs, including accelerometry, GPS mobility patterns, and human-computer interaction (HCI) logs, are transformed by machine learning algorithms into objective ”digital biomarkers.” The reviewed literature demonstrates that these biomarkers—specifically sleep-wake cycle fragmentation, life-space contraction, and semantic shifts in typing—can successfully predict depressive relapse, differentiate bipolar mania from ADHD, and quantify suicide risk with high sensitivity. Crucially, these digital signals often precede subjective symptom reporting by 7–10 days, offering a vital window for Just-in-Time Adaptive Interventions (JITAIs). However, the translation of these computational insights into routine clinical practice faces significant ”last mile” challenges, including the integration of high-velocity data into Electronic Health Records (EHRs), the risk of clinician alarm fatigue, and ethical concerns regarding patient privacy and the socioeconomic ”digital divide.” We conclude that while digital phenotyping offers a revolutionary stethoscope for the mind, its successful adoption requires a hybrid framework where Artificial Intelligence augments, rather than replaces, the therapeutic alliance. This review provides a strategic roadmap for moving the field from passive sensing to proactive, preventative clinical care.
EVOLUTION OF THE COSMIC MICROWAVE BACKGROUND POWER SPECTRUM ACROSS<i>WILKINSON MICROWAVE ANISOTROPY PROBE</i>DATA RELEASES: A NONPARAMETRIC ANALYSIS

Using a nonparametric function estimation methodology, we present a comparative analysis of the Wilkinson Microwave Anisotropy Probe (WMAP) 1-, 3-, 5-, and 7-year data releases for the cosmic microwave background (CMB) angular power spectrum with respect to the following key questions. (1) How well is the power spectrum determined by the data alone? (2) How well is the {Lambda}CDM model supported by a model-independent, data-driven analysis? (3) What are the realistic uncertainties on peak/dip locations and heights? Our results show that the height of the power spectrum is well determined by data alone for multipole l approximately less than 546 (1-year), 667 (3-year), 804 (5-year), and 842 (7-year data). We show that parametric fits based on the {Lambda}CDM model are remarkably close to our nonparametric fits in l-regions where data are sufficiently precise. In contrast, the power spectrum for an H{Lambda}CDM model is progressively pushed away from our nonparametric fit as data quality improves with successive data realizations, suggesting incompatibility of this particular cosmological model with respect to the WMAP data sets. We present uncertainties on peak/dip locations and heights at the 95% (2{sigma}) level of confidence and show how these uncertainties translate into hyperbolic 'bands' on the acoustic scalemore » (l{sub A} ) and peak shift ({phi}{sub m}) parameters. Based on the confidence set for the 7-year data, we argue that the low-l upturn in the CMB power spectrum cannot be ruled out at any confidence level in excess of about 10% ( Almost-Equal-To 0.12{sigma}). Additional outcomes of this work are a numerical formulation for minimization of a noise-weighted risk function subject to monotonicity constraints, a prescription for obtaining nonparametric fits that are closer to cosmological expectations on smoothness, and a method for sampling cosmologically meaningful power spectrum variations from the confidence set of a nonparametric fit.« less
NISQ+: Boosting quantum computing power by approximating quantum error correction

Quantum computers are growing in size, and design decisions are being made now that attempt to squeeze more computation out of these machines. In this spirit, we design a method to boost the computational power of near-term quantum computers by adapting protocols used in quantum error correction to implement "Approximate Quantum Error Correction (AQEC)." By approximating fully-fledged error correction mechanisms, we can increase the compute volume (qubits $\times$ gates, or "Simple Quantum Volume (SQV)") of near-term machines. The crux of our design is a fast hardware decoder that can approximately decode detected error syndromes rapidly. Specifically, we demonstrate a proof-of-concept that approximate error decoding can be accomplished online in near-term quantum systems by designing and implementing a novel algorithm in Single-Flux Quantum (SFQ) superconducting logic technology. This avoids a critical decoding backlog, hidden in all offline decoding schemes, that leads to idle time exponential in the number of T gates in a program. Our design utilizes one SFQ processing module per physical qubit. Employing state-of-the-art SFQ synthesis tools, we show that the circuit area, power, and latency are within the constraints of contemporary quantum system designs. Under pure dephasing error models, the proposed accelerator and AQEC solution is able to expand SQV by factors between 3,402 and 11,163 on expected near-term machines. The decoder achieves a $5\%$ accuracy-threshold and pseudo-thresholds of $\sim$ $5\%, 4.75\%, 4.5\%,$ and $3.5\%$ physical error-rates for code distances $3, 5, 7,$ and $9$. Decoding solutions are achieved in a maximum of $\sim 20$ nanoseconds on the largest code distances studied. By avoiding the exponential idle time in offline decoders, we achieve a $10$x reduction in required code distances to achieve the same logical performance as alternative designs.
Additional file 1 of The pattern of histone H3 epigenetic posttranslational modifications is regulated by the VRK1 chromatin kinase

Additional file 1. Fig. S1: Effect of VRK1 depletion on the epigenetic modifications of H3K9 in the presence (top) or absence (bottom) of serum in A549 lung adenocarcinoma cells.
A Study on the Identification of Artificial Intelligence-generated Content Works and Copyright Attribution: Taking Sora, a Large Model of Text-generated Video, as an Example

The emergence of a large model of text-generated video, represented by Sora, sheds new light on the identification of works and the discussion of copyright attribution of AI-generated content. Under "anthropocentrism", works protected by copyright law have the requirement of originality, so whether the content generated by AI in text-generated videos meets the requirement of originality is of great significance for the determination of works.  In addition, determining the copyright attribution of AI-generated content is conducive to the division of rights and obligations over AI-generated content. Based on the literature research method, this paper argues that as a tool for the creation of human spiritual products, the content generated by the text-generated video big model constitutes a work. And on the issue of copyright attribution, this paper argues that the model of meaning autonomy priority and agreement attribution should be adopted to determine the attribution of copyright.
The onset of long‐term cosmic ray modulation in cycle 23 coupled with a transient increase of anomalous cosmic rays in the distant heliosphere

The onset of significant solar activity in cycle 23 began in November 1997 with several modest events and was followed by an enhanced period of solar activity in April and May 1998. This latter series of events produced a well‐defined step decrease in the cosmic ray intensity at 1 AU as observed by the Goddard Cosmic Ray Experiment on IMP 8. Over the ensuing 2 years there are further decreases in the IMP 8 data with the cumulative effect being in good agreement with the net decrease in cycle 21 at a similar time in the solar cycle. At Voyager 1 (72 AU, 34°N) and Voyager 2 (56 AU, 24°S) there are transient increases in the intensity of 1.8–2.8 MeV H that mark the passage of a large interplanetary disturbance around 1998.75 that was most probably associated with the April–May activity. However, there was no durable decrease observed at that time in the galactic or anomalous cosmic rays. What is unique about this event at Voyager 2 (V 2) in the outer heliosphere is the precursor increase in the anomalous cosmic ray intensity associated with this interplanetary disturbance as defined by the V 2 magnetic field observations. This enhancement event establishes that reacceleration of anomalous cosmic rays can occur in the outer heliosphere. The onset of durable modulation at V 2 begins around 1999.5, probably in association with the disturbances that produced the second step‐like decrease at 1 AU. At Voyager 1 there is preliminary evidence that the corresponding onset time is 1999.85.
Dark matter and the LHC

Cosmological and astrophysical measurements indicate that the universe contains a large amount of dark matter. A number of weak scale dark matter candidates have been proposed in extensions of the standard model. The potential to discover the dark matter particle and determine its properties at the upcoming LHC is summarized.
In Search of Racial Equality: The Elimination of Racial Discrimination

On the face of it, racial discrimination would appear to be an issue in which the United Nations could take effective action. It is a matter on which there is considerable consensus among governments that, on the basis of a broadly supported convention, have a mandate to enforce internationally agreed norms to eliminate racial discrimination. For that matter, who but those on the lunatic fringes of today’s world still defend the right to discriminate by reason of race after the horror of Nazism, the history of slavery and the end of colonial empires? The answer may seem obvious. The reality, however, is somewhat different.
Learning Active Subspaces and Discovering Important Features with Gaussian Radial Basis Functions Neural Networks

Providing a model that achieves a strong predictive performance and is simultaneously interpretable by humans is one of the most difficult challenges in machine learning research due to the conflicting nature of these two objectives. To address this challenge, we propose a modification of the radial basis function neural network model by equipping its Gaussian kernel with a learnable precision matrix. We show that precious information is contained in the spectrum of the precision matrix that can be extracted once the training of the model is completed. In particular, the eigenvectors explain the directions of maximum sensitivity of the model revealing the active subspace and suggesting potential applications for supervised dimensionality reduction. At the same time, the eigenvectors highlight the relationship in terms of absolute variation between the input and the latent variables, thereby allowing us to extract a ranking of the input variables based on their importance to the prediction task enhancing the model interpretability. We conducted numerical experiments for regression, classification, and feature selection tasks, comparing our model against popular machine learning models, the state-of-the-art deep learning-based embedding feature selection techniques, and a transformer model for tabular data. Our results demonstrate that the proposed model does not only yield an attractive prediction performance compared to the competitors but also provides meaningful and interpretable results that potentially could assist the decision-making process in real-world applications. A PyTorch implementation of the model is available on GitHub at the following link. https://github.com/dannyzx/Gaussian-RBFNN