ethicalabs/Research-Intent-Collab huggingface dataset:
Proposal for a radiation shielding study aiming the implantation of neutrons beam shutter in the J-9 radiation channel of the Argonauta reactor of the Nuclear Engineering Institute.

Argonauta, the only nuclear research reactor situated in Rio de Janeiro, located at the Institute of Nuclear Engineering (IEN), regularly serves a network of users focused on research and development, and also provides its infrastructure for experimental classes and completion work course. Due to increasing demand for non-destructive thermal neutron assays and production of radioisotopes, there is a search for new procedures and/or devices that optimize users' exposure to neutrons. The implementation of mechanisms that allow access to the irradiation channels without the reactor being turned off and with a shielding configuration that limits the occupational doses at this location is very useful for the operation of the reactor. In order to achieve this, the present work proposes the establishment of a neutron beam shutter of the J-9 irradiation channel of the IEN’s Argonauta reactor. In a first step, experimental measurements were made in the irradiation channel of the reactor using a BF3 detector, which is coupled to a spectrometer. In this phase, the neutron beam was aligned to the spectrometer, and different materials were used as shields, aiming the attenuation of the beam. To validate and/or change the configuration of the barrier that best meets the material irradiation needs, a second planned phase is involving the neutron flux simulation of the reactor and the various shields with different boundary conditions using the particle transport code, Monte Carlo N-Particle Extended (MCNP- X).
Intention to explore the role of discretization in the emergence of self-organization in certain approximations of continuous cellular automata and other complex dynamic systems

John H. Conway's Game of Life, as well as cellular automata in the larger family of Life-like CA, are discrete: the cells have a binary state space and the birth and survival transition rules are 9-bits apiece. Inspired by Life, several projects have developed continuously-valued cellular automata frameworks in 2 dimensions. These CA systems are necessarily imperfect approximations of ideal continuous systems when they are implemented in a digital computer, and this inevitably leads to discretization errors. As we know since at least the time of Poincairé's work on the three-body problem, arbitrarily small errors in a complex dynamic system can lead to substantial behavioral deviation over time. This outline of intent is based on observations in cellular automata that, in certain cases, errors are not only well-tolerated, but are essential for self-organization. This manuscript describes a set of experiments to investigate the importance of discretization in approximating continuously valued dynamic systems, how and when discretization is required for self-organization to occur, and the relevance the results might have with respect to emergent agency and analogies for consciousness.
Exploring the quality of Life at the end of Life (Qual-E) Instrument with Australian Palliative Care Hospital Patients: Hurdles and Directions

The provision of care that enhances the quality of life at the end of life is a fundamental goal of palliative care services. This pilot study explored the application of the Quality of Life at the End of Life (QUAL-E) instrument in a sample of 52 patients who were hospitalized in two metropolitan Western Australian hospitals. Participants were given the option to complete the QUAL-E either as a self-report (n=9, 17.3 percent) or, aided by a research assistant, as a structured interview (n=43, 82.7 percent). The instrument demonstrated patient acceptability and face validity, particularly when it was administered with the assistance of a research assistant. Despite having difficulty with some questions, patients expressed their appreciation at being given the opportunity to contribute to the research and to reflect upon and give voice to their thoughts and feelings. Health practitioners indicated that the instrument could be a valuable tool for holistic assessment and service evaluation. We suggest that minor changes be made to the QUAL-E before it is used further in an Australian context; we also recommend that this instrument be tested in other settings and populations.
Scene Splatter: Momentum 3D Scene Generation from Single Image with Video Diffusion Model

CVPR 2025
Situating dissemination and implementation sciences within and across the translational research spectrum

AbstractThe efficient and effective movement of research into practice is acknowledged as crucial to improving population health and assuring return on investment in healthcare research. The National Center for Advancing Translational Science which sponsors Clinical and Translational Science Awards (CTSA) recognizes that dissemination and implementation (D&amp;I) sciences have matured over the last 15 years and are central to its goals to shift academic health institutions to better align with this reality. In 2016, the CTSA Collaboration and Engagement Domain Task Force chartered a D&amp;I Science Workgroup to explore the role of D&amp;I sciences across the translational research spectrum. This special communication discusses the conceptual distinctions and purposes of dissemination, implementation, and translational sciences. We propose an integrated framework and provide real-world examples for articulating the role of D&amp;I sciences within and across all of the translational research spectrum. The framework’s major proposition is that it situates D&amp;I sciences as targeted “sub-sciences” of translational science to be used by CTSAs, and others, to identify and investigate coherent strategies for more routinely and proactively accelerating research translation. The framework highlights the importance of D&amp;I thought leaders in extending D&amp;I principles to all research stages.
Natural Language Processing in Radiology: A Systematic Review

Radiological reporting has generated large quantities of digital content within the electronic health record, which is potentially a valuable source of information for improving clinical care and supporting research. Although radiology reports are stored for communication and documentation of diagnostic imaging, harnessing their potential requires efficient and automated information extraction: they exist mainly as free-text clinical narrative, from which it is a major challenge to obtain structured data. Natural language processing (NLP) provides techniques that aid the conversion of text into a structured representation, and thus enables computers to derive meaning from human (ie, natural language) input. Used on radiology reports, NLP techniques enable automatic identification and extraction of information. By exploring the various purposes for their use, this review examines how radiology benefits from NLP. A systematic literature search identified 67 relevant publications describing NLP methods that support practical applications in radiology. This review takes a close look at the individual studies in terms of tasks (ie, the extracted information), the NLP methodology and tools used, and their application purpose and performance results. Additionally, limitations, future challenges, and requirements for advancing NLP in radiology will be discussed.
Stability of real parametric polynomial discrete dynamical systems

We extend and improve the existing characterization of the dynamics of general quadratic real polynomial maps with coefficients that depend on a single parameter $λ$, and generalize this characterization to cubic real polynomial maps, in a consistent theory that is further generalized to real $m$-th degree real polynomial maps. In essence, we give conditions for the stability of the fixed points of any real polynomial map with real fixed points. In order to do this, we have introduced the concept of Canonical Polynomial Maps which are topologically conjugate to any polynomial map of the same degree with real fixed points. The stability of the fixed points of canonical polynomial maps has been found to depend solely on a special function termed Product Position Function for a given fixed point. The values of this product position determine the stability of the fixed point in question, when it bifurcates, and even when chaos arises, as it passes through what we have termed stability bands. The exact boundary values of these stability bands are yet to be calculated for regions of type greater than one for polynomials of degree higher than three.
Thermo-Optic Phase Shifter for Photonic Neural Networks

We experimentally demonstrate a compact and power efficient (Pπ = 21 mW) silicide-based thermo-optic phase shifter of length 96 µm for photonic neural networks.
Third Time's the Charm? Image and Video Editing with StyleGAN3

StyleGAN is arguably one of the most intriguing and well-studied generative models, demonstrating impressive performance in image generation, inversion, and manipulation. In this work, we explore the recent StyleGAN3 architecture, compare it to its predecessor, and investigate its unique advantages, as well as drawbacks. In particular, we demonstrate that while StyleGAN3 can be trained on unaligned data, one can still use aligned data for training, without hindering the ability to generate unaligned imagery. Next, our analysis of the disentanglement of the different latent spaces of StyleGAN3 indicates that the commonly used W/W+ spaces are more entangled than their StyleGAN2 counterparts, underscoring the benefits of using the StyleSpace for fine-grained editing. Considering image inversion, we observe that existing encoder-based techniques struggle when trained on unaligned data. We therefore propose an encoding scheme trained solely on aligned data, yet can still invert unaligned images. Finally, we introduce a novel video inversion and editing workflow that leverages the capabilities of a fine-tuned StyleGAN3 generator to reduce texture sticking and expand the field of view of the edited video.
Alternative Dispute Settlement and the Jurisprudential Legacy of the World Trade Organization’s Appellate Body

This article analyses the possible impact of the disputes advanced through the Multiparty Interim Appeal Arbitration Arrangement (‘MPIA’) and preferential trade agreements (‘PTAs’) on the jurisprudential legacy of the Appellate Body (‘AB’) and shows that those alternative dispute settlement mechanisms can play a significant role in preserving and further developing World Trade Organization’s (‘WTO’) case law. In the future, the importance of alternative dispute settlement mechanisms resolving arguments of international trade law is bound to increase (especially, in light of the ongoing deadlock at the WTO). That said, this does not come without risks for the (much disputed) coherence of WTO precedence by way of departure from established interpretations of the WTO acquis. Ultimately, it is the quality of the alternative dispute settlement awards that will determine the extent to which the jurisprudential legacy of the AB will be maintained. This article demonstrates that alternative dispute settlement mechanisms pose both challenges and opportunities for the consistency of the WTO case law. This article sheds further light on the potential risks and virtues pertaining to each one of them and argues that until the functioning of the Appellate Body is restored, alternative dispute adjudicating bodies must observe its jurisprudential legacy to promote legal certainty and predictability in international trade dispute settlement. WTO Dispute Settlement, Alternative Dispute Settlement, Appellate Body, Multiparty Interim Appeal Arbitration Arrangement, Preferential Trade Agreements
The Responsibility to Protect, Rhetoric, Reality and the Future of Humanitarian Intervention

Anyone reading this book should start with chapter 6. Here the author sets out to explain that he believes in the righteousness of humanitarian intervention and why. The chapter serves as pivot to ...
The Amplification of Generative Artificial Intelligence (AI) in Content Marketing For Women Micro-Entrepreneurs: Qualitative Case Study Approach

Background: The integration of Generative Artificial Intelligence (AI) in content marketing had gained increasing attention as a key driver of digital transformation, particularly for women-led microenterprises. Purpose: This study investigates the role of generative artificial intelligence (AI) in optimizing content marketing strategies to accelerate the digitalization of female-owned microbusinesses in Indonesia. Design/methodology/approach: Using qualitative research methods, including in-depth interviews with 5 (five) participants women micro-entrepreneurs, the study emphasizes the depth of context. This study explores the challenges and benefits of adopting AI-driven content creation tools. The analytical method used is holistic coding.   Findings/results: The results reveal that Generative AI significantly enhances content production in terms of creativity, relevance, and efficiency, while also improving audience engagement and brand visibility. These findings confirm that in content creation, it is no longer necessary to pay third parties to create content, and women entrepreneurs can automatically generate the marketing content they need at no cost. Furthermore, this study highlights how AI acts as a powerful catalyst for social and economic empowerment by providing micro-businesses with the tools necessary to compete in the digital economy.  Conclusion: The research findings emphasize the transformative potential of AI in reshaping traditional marketing approaches, fostering greater inclusivity and growth in the entrepreneurial landscape. Although these entities have implemented generative AI technologies to augment the production of marketing materials, they are currently lack the specialized competency in prompt composition required to optimize the conversion potential of the resulting content for marketing purposes. Through its relevant institutions, the government is strategically promoting digital transformation by establishing dedicated digital and AI learning centers in some regions. According to the informants, however, these initiatives seldom reach female-owned micro-businesses in those same regions. Originality/value: By shedding light on the specific impact of AI on women micro-entrepreneurs, this study contributes to the broader discourse on gender, entrepreneurship, and technological innovation. The implications of this research offer valuable insights for policymakers, business practitioners, and stakeholders aiming to support the digital transformation of women-led micro-enterprises. Keywords: Generative AI, content marketing, digital skill, digital transformation, women micro-entrepreneurs
Accuracy and robustness of a plant-level cabbage yield prediction system generated by assimilating UAV-based remote sensing data into a crop simulation model

Abstract                                        In-season crop growth and yield prediction at high spatial resolution are essential for informing decision-making for precise crop management, logistics and market planning in horticultural crop production. This research aimed to establish a plant-level cabbage yield prediction system by assimilating the leaf area index (LAI) estimated from UAV imagery and a segmentation model into a crop simulation model, the WOrld FOod STudies (WOFOST). The data assimilation approach was applied for one cultivar in five fields and for another cultivar in three fields to assess the yield prediction accuracy and robustness. The results showed that the root mean square error (RMSE) in the prediction of cabbage yield ranged from 1,314 to 2,532 kg ha                     –1                     (15.8–30.9% of the relative RMSE). Parameter optimisation via data assimilation revealed that the reduction factor in the gross assimilation rate was consistently attributed to a primary yield-limiting factor. This research further explored the effect of reducing the number of LAI observations on the data assimilation performance. The RMSE of yield was only 107 kg ha                     –1                     higher in the four LAI observations obtained from the early to mid-growing season than for the nine LAI observations over the entire growing season for cultivar ‘TCA 422’. These results highlighted the great possibility of assimilating UAV-derived LAI data into crop simulation models for plant-level cabbage yield prediction even with LAI observations only in the early and mid-growing seasons.
Human resources information system (HRIS)-enabled human resource management (HRM) performance : a business process management (BPM) perspective

It is widely accepted that business process management (BPM), a contemporary management approach that focuses on managing overall business processes within an organization to accomplish the organizational goal, relies on modern information and communication technology (ICT) systems. Although there are plenty of academic discussions available on BPM and the firm performance relationship, the literature does not provide constructive information on how the adoption of ICT impacts the BPM performance. Therefore, this study creates an awareness of the contribution of ICT to BPM by analyzing the linkage between impacts of human resource information systems (HRIS) on human resource management (HRM) performance. A conceptual model was developed with strong theoretical background by incorporating the works informed by Lee et al. (2012) and Paauwe and Richardson (1997) to test several hypotheses. In this research, the target population is human resources professionals who have access to HRIS within their organizations in a Canadian context. Since this study has a wide range of data distribution that tries to measure the strength of relationship between a HRIS-enabled HR practices and the HRM performance, this study adopts Kendall’s tau-b correlation, one of the best approaches to measure the strength of the relationship. The important findings of this study are that HRIS-enabled HR transactional, traditional and transformational practices, when implemented appropriately, significantly impact the HRM performance. Specifically, this study confirms that HRIS-enabled HR traditional management practices such as performance management, rewards, career development and communication predominantly significantly impact the HRM performance. In other words, this study specifically encourages an organization to adopt comprehensive performance management systems (PMS), an important component of HRIS, to manage their employees effectively.
The time for cost-effectiveness in the new European Union member states: the development and role of health economics and technology assessment in the mirror of the Hungarian experience

Sophisticated methodology and research centres of health economics and health technology assessment were established in the developed countries over the past 30 years, releasing more and more studies of better and better quality every year. A crucial factor in health policy and reimbursement decisions in these countries is cost-effectiveness results. Due to methodological diversification, results of locally performed health economics studies are constrained in international utility. This fact encourages us to set the current goal of greatest importance, i.e. to standardise country-specific methods, thereby promoting transferability and adaptability of results, being backed by each important health care organisation all over Europe. The situation in the new member states [European Union (EU)12] is profoundly different compared with EU15. In these countries, neither the necessary research institutions nor professionals are in place in sufficient numbers; even in most EU12 countries, the importance of cost-effectiveness has not yet been realised. The present study focuses mainly on the EU12. These countries are absolutely dependent on cost-effectiveness results from abroad, and this seems to persist in the long-term. Transferability and adaptability of the results of health economics studies carried out elsewhere through European collaboration is vital for these countries.
CORPORATE SOCIAL RESPONSIBILITY: PERFORMANCE AND REPORTING

Corporate social responsibility is not a new issue. The main aim of a company is to minimise the costs and maximize profits. On the other hand, ethical business people recognise their responsibility to the public and to themselves. Fulfilment of these responsibilities constitutes ethical and socially responsible behaviour. Although corporate social performance (CSP) has been used for several years in the business and society literature, in many cases it has been used synonymously with corporate social responsibility, corporate social responsiveness, or any other interaction between business and the social environment. This study will briefly examine the corporate social responsibility, the performance and reporting issues.
Zero-Energy Fluctuation Dark Matter (ZEFD) Model: Quantum Field Theory, Dynamical Equations, Observational Tests and Cosmological Numerical Simulation

Zero-Energy Fluctuation Dark Matter (ZEFD) Model: A Unified Framework for Cosmic Structure, Dark Matter, Cosmic Acceleration, and Black Hole Evaporation     This paper presents the complete, self-contained Zero-Energy Fluctuation Dark Matter (ZEFD) model—a unified theoretical framework for cosmic structure, dark matter, cosmic acceleration, and black hole evaporation. Constructed on primordial quantum fluctuations, strict global zero-energy balance, and cosmic expansion-freezing effects, the model avoids introducing new fundamental particles, new fields, or dark energy.     We provide the full quantum field theory derivation in curved FRW spacetime, including the Lagrangian, equation of motion, energy-momentum tensor, and quantization of the primordial scalar field. A closed, parameter-free system of dynamical equations is established to describe cosmic expansion, matter formation, and residual dark fluctuation evolution.     The ZEFD model exhibits quantitative consistency with high-precision cosmological observations: Planck CMB power spectra, baryon acoustic oscillations (BAO), cosmic shear gravitational lensing, and flat galaxy rotation curves exemplified by NGC 3198. A comprehensive cosmological numerical simulation scheme, compatible with large-scale supercomputers, is developed using standard Particle-Mesh (PM) N-body and grid fluid algorithms.     In the ZEFD model, dark matter is not an exotic particle but the un-collapsed, spacetime-correlated residual of primordial quantum fluctuations that share the same origin as baryonic matter. The model further establishes a causal mechanism: cosmic expansion modifies vacuum fluctuations near black hole horizons and drives Hawking radiation as a local dynamical mapping of cosmic expansion.     The ZEFD model satisfies general covariance and quantum field theory principles, reproduces all observational successes of the ΛCDM model with greater theoretical economy, and naturally explains the persistent null results of dark matter direct-detection experiments.