ethicalabs/Research-Intent-Collab huggingface dataset:
AI Contextual Information Shapes Moral and Aesthetic Judgements of AI-Generated Visual Art Professor of Cognitive and Social Neuroscience

Throughout history, art creation has been regarded as a uniquely human means to express original ideas, emotions, and experiences. However, as Generative Artificial Intelligence reshapes visual, aesthetic, legal, and economic culture, critical questions arise about the moral and aesthetic implications of AI-generated art. Despite the growing use of AI tools in art, their moral impact remains underexplored. Understanding moral judgments of AI-generated art is essential for assessing AI's impact on art and its alignment with ethical norms. Across three pre-registered experiments combining explicit and implicit paradigms with Bayesian modelling, we examined how information about AI systems influences moral and aesthetic judgments and whether human art is implicitly associated with positive attributes compared to AI-generated art. Experiment 1 revealed that factual information about AI backend processes reduced moral acceptability and aesthetic appeal in contexts such as gaining financial incentives and art status. Experiment 2 showed that additional information about AI art's success had no clear impact on moral judgments. Experiment 3 demonstrated that an implicit association task did not reliably link human art with positive attributes and AI art with negative ones. These findings show that factual information about AI systems shapes judgments, while varying information doses about AI art's success have limited moral impact. Additionally, implicit associations between human-made and AI-generated art are similar. This work enhances understanding of moral and aesthetic perceptions of AI-generated art, emphasizing the importance of examining human—AI interactions in an art context, and their current societal implications.
The dark side of transparency: Problematising the Nigeria Extractive Industries Transparency Initiative as a Public Sector Transparency, Accountability and Anti-Corruption Initiative

This study explores the dark side of transparency by problematizing the Nigeria Extractive Industries Transparency Initiative (NEITI) as a transparency, accountability and anti-corruption initiative in Nigeria. It does this by interrogating the underlying assumptions that transparency in the form of increased information disclosure inevitably leads to enhanced accountability and reduced corruption. Theoretic insights are drawn from the transparency literature as well as from the International Accounting Standards Board's framework for financial reporting. The findings enable a more nuanced understanding of transparency – where and when transparency works, and where and when it may lead to unintended outcomes. They show how increased information disclosure conceals and legitimises the weak and corrupt reporting systems and practices of government agencies. They highlight the importance of understandability of information disclosed as a key requirement of transparency. They illustrate that transparency is a complex social process by highlighting the means by which the government tries to gain control of the NEITI organisation and how NEITI's ability to operate effectively is dependent on the political will of the government in power. The findings also demonstrate that the instrument through which transparency is enacted is itself a central actor in the transparency process as historical corruption within the NEITI bureaucracy as well as the opacity of NEITI as an organisation lead to outcomes of distrust, uncertainty and doubt amongst NEITIs target audience.
Culturally tailored interventions in adults with obesity: a protocol for a systematic review with meta-analysis and qualitative evidence synthesis

Introduction                     Obesity disproportionately affects ethnic minority populations due to structural inequalities, such as limited access to healthy food, inadequate healthcare and systemic racism. Universal weight management programmes often fail to meet the unique needs of ethnic minority populations. These universal interventions may lead to lower engagement and poorer health outcomes compared with those observed in non-minoritised ethnic groups. This systematic review will examine the impact of culturally tailored interventions to treat and manage obesity in adult ethnic minority populations on weight- and health-related outcomes (meta-analysis) and patient experience (qualitative evidence synthesis).                                                           Methods and analysis                     The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines will be followed. Interventions of interest will include standalone or multicomponent behavioural interventions with culturally tailored elements of design or delivery. These will be compared against standard weight management interventions or usual care in adults from ethnic minority populations living with obesity. The primary outcome is the mean percentage weight (kg) change between pre–post interventions. A search of databases (Ovid MEDLINE, Embase, APA PsycINFO, Scopus and Web of Science) was conducted in February 2025. Eligible studies include randomised controlled trials (RCTs), quasi-experimental (non-randomised trials, pre–post interventions) and qualitative research. Risk of bias will be assessed with the Cochrane Risk of Bias 2 tool and the Mixed Methods Appraisal Tool. Narrative synthesis will be performed according to the synthesis without meta-analysis guidelines. For eligible RCTs, a random-effects meta-analysis will calculate pooled effect sizes between pre–post intervention using standardised mean differences, with additional sensitivity and subgroup analyses. Qualitative evidence synthesis will be performed using semi-automated text analytics (unsupervised machine learning) and inductive thematic analysis.                                                           Ethics and dissemination                     Ethical approval is not required. Findings will be disseminated through peer-reviewed journal publications, conference presentations, professional organisations and patient and public networks.                                                           PROSPERO registration number                     CRD42025636750.
Self-supervised Representation Learning for Astronomical Images

Abstract                Sky surveys are the largest data generators in astronomy, making automated tools for extracting meaningful scientific information an absolute necessity. We show that, without the need for labels, self-supervised learning recovers representations of sky survey images that are semantically useful for a variety of scientific tasks. These representations can be directly used as features, or fine-tuned, to outperform supervised methods trained only on labeled data. We apply a contrastive learning framework on multiband galaxy photometry from the Sloan Digital Sky Survey (SDSS), to learn image representations. We then use them for galaxy morphology classification and fine-tune them for photometric redshift estimation, using labels from the Galaxy Zoo 2 data set and SDSS spectroscopy. In both downstream tasks, using the same learned representations, we outperform the supervised state-of-the-art results, and we show that our approach can achieve the accuracy of supervised models while using 2–4 times fewer labels for training. The codes, trained models, and data can be found at https://portal.nersc.gov/project/dasrepo/self-supervised-learning-sdss.
Heat-related mortality risk model for climate change impact projection

We previously developed a model for projection of heat-related mortality attributable to climate change. The objective of this paper is to improve the fit and precision of and examine the robustness of the model.We obtained daily data for number of deaths and maximum temperature from respective governmental organizations of Japan, Korea, Taiwan, the USA, and European countries. For future projection, we used the Bergen climate model 2 (BCM2) general circulation model, the Special Report on Emissions Scenarios (SRES) A1B socioeconomic scenario, and the mortality projection for the 65+-year-old age group developed by the World Health Organization (WHO). The heat-related excess mortality was defined as follows: The temperature-mortality relation forms a V-shaped curve, and the temperature at which mortality becomes lowest is called the optimum temperature (OT). The difference in mortality between the OT and a temperature beyond the OT is the excess mortality. To develop the model for projection, we used Japanese 47-prefecture data from 1972 to 2008. Using a distributed lag nonlinear model (two-dimensional nonparametric regression of temperature and its lag effect), we included the lag effect of temperature up to 15 days, and created a risk function curve on which the projection is based. As an example, we perform a future projection using the above-mentioned risk function. In the projection, we used 1961-1990 temperature as the baseline, and temperatures in the 2030s and 2050s were projected using the BCM2 global circulation model, SRES A1B scenario, and WHO-provided annual mortality. Here, we used the "counterfactual method" to evaluate the climate change impact; For example, baseline temperature and 2030 mortality were used to determine the baseline excess, and compared with the 2030 excess, for which we used 2030 temperature and 2030 mortality. In terms of adaptation to warmer climate, we assumed 0 % adaptation when the OT as of the current climate is used and 100 % adaptation when the OT as of the future climate is used. The midpoint of the OTs of the two types of adaptation was set to be the OT for 50 % adaptation.We calculated heat-related excess mortality for 2030 and 2050.Our new model is considered to be better fit, and more precise and robust compared with the previous model.
Regional Organisations' Representation in the United Nations Security Council Influence on the Security Council's Agenda-setting

When violence against civilians is high in armed conflicts, it is predicted that the UNSC will pay close attention to those conflicts. However, it does not always happen to an equal degree. Based on recently collected data of UNSC agenda-setting behaviour by Susan H. Allen and Amy T. Yuen, this paper asks: why do some conflicts receive more UNSC attention than others, despite similar levels of violence against civilians? The thesis looks into the role of ROs in the UNSC agenda-setting. To account for the variation, the thesis argues that ROs are able to influence the UNSC agenda-setting in a way that leads some conflicts to have more recurrences of items on the agenda and others less. By applying a structured focused comparison on the conflict in Darfur between 2003 – 2007, and the Rohingya crisis in Myanmar between 2016-2022, I find a correlation between representation of ROs and recurrences of agenda-items. However, correlation is not causation, and I conclude that ROs had little influence in the UNSC decision-making and that it was the interests of the P5 and the institutional role of the UN Secretary-General that lead to the variation in the number of recurrences of items on the agenda.
Self-organization and the Emergence of Complexity in Ecological Systems

Abstract What explains the remarkable regularities in distribution and abundance of species, in size distributions of organisms, or in patterns of nutrient use? How does the biosphere maintain exactly the right conditions necessary for life as we know it? Gaia theory postulates that the biota regulates conditions at levels it needs for survival, but evolutionary biologists reject this explanation because it lacks a mechanistic basis. Similarly, the notion of self-organized criticality fails to recognize the importance of the heterogeneity and modularity of ecological systems. Ecosystems and the biosphere are complex adaptive systems, in which pattern emerges from, and feeds back to affect, the actions of adaptive individual agents, and in which cooperation and multicellularity can develop and provide the regulation of local environments, and indeed impose regularity at higher levels. The history of the biosphere is a history of coevolution between organisms and their environments, across multiple scales o...
China’s changing engagement in global peace building and conflict resolution: drivers and trends

The study aims at providing an in-depth analysis of the drivers of China’s peace building engagement and examining the interactive nature of the various drivers and factors that played remarkable role in increasing China’s economic rise and leadership in the international system. To approach the study goals, descriptive-analytical method has been employed along with Hudson’s foreign policy analysis through which China’s aims and motivations of engaging in peace building are illustrated. The paper concludes that China seeks to shape its great power leadership and identity where the case studies revealed that China’s economic engagement as part of its peace building efforts is increasingly being driven by Chinese great power status and geostrategic security interests. Simultaneously, as seen in the Darfur War, Myanmar, Mali, South Sudan, and Afghanistan, China’s policy towards conflict zones has undergone a tangible and salient transition from one of avoidance to one of increasing interest and engagement
CROSS-DISCIPLINARY ART THROUGH AI-GENERATED MUSIC AND VISUALS

Multimodal generative systems change the current creative practices which is the focus of this study, looking at how the field of cross-disciplinary art has grown rapidly due to AI-generated music and visual synthesis. The study combines the concept of deep learning including GANs, VAEs, and transformer-based networks to learn the interaction between sonic and visual representations that can produce coherent works of art that combine sound, visuals, and real-time engagement. The proposed system, based on different data sets, incorporating annotated music collections, visual art collections, and records of multimodal performances, provides cross-modal associations that match rhythm, timbre, texture, color, and movement. The theoretical base integrates the cognitive theories of perception, emotion and synesthetic experience making AI not just a technical means but a creative partner who can assist new types of computational creativity. It uses a complete workflow pipeline of generative music-visual production, which can be used to create offline productions as well as in real time performance settings. It has a special user interface allowing artists to modulate parameters, control style transfer, and dynamically interact with developing multimodal content. Experimental testing is an integration of quantitative analysis (perceptual coherence, structural similarity, and temporal alignment) and qualitative response by the composers, visual artists and the viewers involved.
High Prevalence of Multidrug-resistant Pathogens in Surgical Site Infections: Implications for Antimicrobial Stewardship

We evaluated distribution of bacterial pathogens isolated from post-operative wounds and their antimicrobial susceptibility profiles. The pus samples were collected from 122 patients clinically diagnosed of having surgical site infections (SSIs). The VITEK 2 COMPACT system was used for susceptibility testing. The cefoxitin screening was used to identify production of Extended-Spectrum β-Lactamase (ESBL) and Methicillin-Resistant Staphylococcus aureus (MRSA). The most prevalent organism was Staphylococcus aureus (33.6%), followed by Escherichia coli (10.7%), Pseudomonas aeruginosa (15.6%) and Klebsiella spp. (27.9%). With 74% of S. aureus strains being MRSA, high resistance to ciprofloxacin (91%) and benzylpenicillin (91%) was observed. Although 37% of Gram-negative isolates were carbapenem resistant, they were most sensitive to meropenem (63%), imipenem (59%) and cefepime (55%). Majority of Gram-negative isolates (56.4%) were ESBL positive indicating widespread β-lactamasemediated resistance. Pseudomonas aeruginosa (73.7%) and Klebsiella spp. (58.9%) were the predominant ESBL producers followed by Escherichia coli (61.5%). The highest cases occurred in the cleancontaminated wounds (45.08%) followed by contaminated (22.95%) and clean wounds (18.03%). The SSIs were predominantly caused by MRSA and ESBL-producing Gram-negative bacteria. The pathogens remained susceptible to vancomycin, linezolid, daptomycin, teicoplanin, meropenem, imipenem and cefepime indicating that these agents are still effective treatment options
Patient-reported outcomes (PROs) and health-related quality of life (HRQoL) with taletrectinib in advanced ROS1+ non-small cell lung cancer (NSCLC) from the TRUST-II study.

8629                                                           Background:                     Taletrectinib is a next-generation, CNS-active, selective ROS1 tyrosine kinase inhibitor (TKI) approved by the US FDA for the treatment of patients with locally advanced or metastatic ROS1+ NSCLC based on results from two Phase 2 studies, TRUST-I (NCT04395677) and TRUST-II (NCT04919811). Here we report PROs with taletrectinib from TRUST-II.                     Methods:                     Patients with locally advanced or metastatic ROS1+ NSCLC were treated with taletrectinib 600 mg once daily in 21-day cycles. HRQoL and PROs for cancer-specific symptoms were evaluated using the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire 30-item core module (QLQ-C30) and 13-item lung cancer module (QLQ-LC13). Questionnaires were only distributed to patients from North America and Europe. Data were collected at screening, then subsequently on Day (D)1 of every cycle (C) until C9D1, on D1 of every three cycles until C27D1, and every four cycles thereafter until the end of treatment (within 7 days of last dose). Changes from baseline over time were summarized using descriptive statistics. A change in score of ≥10 points from baseline was considered clinically meaningful. Time to first improvement (TFI) was assessed using Kaplan–Meier methods.                     Results:                     At data cutoff (August 31, 2025), the analysis set included 69 patients (23 TKI-naïve and 46 TKI-pretreated). Mean changes from baseline improved or remained stable for most domains across both questionnaires. For global health status/quality of life, the majority of patients showed clinically meaningful improvement or remained stable at multiple timepoints assessed (e.g. 74% of patients at C7). Mean cognitive function score improved or remained stable throughout treatment, with the majority (63–77%) of patients showing improvement or stability and only 9–23% of patients showing worsening at various assessment times. Common disease-related symptoms, including pain and fatigue (QLQ-C30), and dyspnea and coughing (QLQ-LC13), showed consistent clinically meaningful improvement throughout treatment, with a median TFI of 1–3 months across all patients. Coughing was particularly improved in TKI-naïve patients, with a median TFI of &lt; 1 month.                     Conclusions:                     Taletrectinib was associated with improved or stable HRQoL in the majority of patients and with rapid relief of disease-related symptoms. In contrast to other ROS1 TKIs, taletrectinib demonstrated preservation of cognitive function over time. Together with the efficacy and safety results, these data further support the use of taletrectinib for patients with ROS1+ NSCLC.                                            Clinical trial information:                       NCT04919811                                          .
A review of the stable isotope bio-geochemistry of the global silicon cycle and its associated trace elements

Silicon (Si) is the second most abundant element in the Earth’s crust and is an important nutrient in the ocean. The global Si cycle plays a critical role in regulating primary productivity and carbon cycling on the continents and in the oceans. Development of the analytical tools used to study the sources, sinks, and fluxes of the global Si cycle (e.g., elemental and stable isotope ratio data for Ge, Si, Zn, etc.) have recently led to major advances in our understanding of the mechanisms and processes that constrain the cycling of Si in the modern environment and in the past. Here, we provide background on the geochemical tools that are available for studying the Si cycle and highlight our current understanding of the marine, freshwater and terrestrial systems. We place emphasis on the geochemistry (e.g., Al/Si, Ge/Si, Zn/Si, d13C, d15N, d18O, d30Si) of dissolved and biogenic Si, present case studies, such as the Silicic Acid Leakage Hypothesis, and discuss challenges associated with the development of these environmental proxies for the global Si cycle. We also discuss how each system within the global Si cycle might change over time (i.e., sources, sinks, and processes) and the potential technical and conceptual limitations that need to be considered for future studies.
Dynamic Concatenation of Quantum Error Correction in Integrated Quantum Computing Architecture

AbstractResource overhead problem caused by concatenation in quantum error correction (QEC) is of significant importance for the realization of fault-tolerant quantum computation (FTQC). To attack this problem, we propose a novel scheme by considering integrated FTQC architecture where the concatenation level is controlled dynamically; i.e., less (or more) concatenation levels are imposed by good (or poor) performance gates—we call this scheme “dynamic concatenation” in this sense. Such a dynamic concatenation is realizable in an integrated structure of FTQC, as the information of the concatenation can be communicated between classical system elements (e.g., compiler and system organizer) and the logical qubits in real-time. We derive the effective lower and upper bounds of the length of gate decomposition in order to achieve the practical advantage, namely of reduction of the overall operation time. By considering two non-trivial examples, it is shown that the aforementioned advantage can indeed be achieved in the presented scheme. Our result also provides an important scientific message, i.e., the interplay between “classical” and “quantum” can be helpful in QEC.
Analysis of Classifications and Characteristic of Additive Manufacturing(3D Print)

The Additive Manufacturing(3D Print) was widely studied and used in recent years, but there wasn’t a systematic, distinct and accurate classification about the Additive Manufacturing. The Additive Manufacturing was divided into 4 sorts and 16 sub sorts according to the category and state of the added materials and heat source of the manufacturing in this paper, as well as the principle, characteristics and trend of the each sorts of the Additive Manufacturing method were analyzed. Both the imperfections of the Additive Manufacturing, such as single material and low efficiency, and trends to multiple materials, high efficient, stable and compatible were presented in the end.
Open and Shared Educational Resources – A Collaborative Strategy for Advancing E-Learning Communities

Advances in information technologies have created unique opportunities for the free exchange of ideas on a global scale. To this end, a growing number of education stakeholders are finding that applying an open source approach to content development provides an extraordinary opportunity to change the curricula paradigm. Access to quality learning materials and the free exchange of knowledge is increasing. The authors explore the increased adoption of open and shared educational resources (OSER), with such examples as Curriki. Curriki extends the model by providing an integrated learning environment and resource repository centered on a culture of collective participation.