ethicalabs/Research-Intent-Collab huggingface dataset:
Decolonizing Irishness: Assertions of Afro-Irish Self-Determination in Nicky Gogan and Paul Rowley’s <i>Seaview</i> and Melatu Uche Okorie’s <i>This Hostel Life</i>

Nicky Gogan and Paul Rowley's 2008 documentary film Seaview and Melatu Uche Okorie's 2018 short-story collection This Hostel Life raise questions about Ireland's postcolonial position on the economic and geographic periphery of Europe amid the added complexity of emerging racial formations. These texts critically depict the racial and cultural barriers that produce a voyeuristic bifurcation between an implied white Irish citizen and a racialized non-citizen. Seaview invokes this voyeuristic bifurcation to critique the segregation and isolation of asylum seekers detained in Direct Provision (DP) centres from the rest of Irish society. Yet moments of ambiguity in filmic strategies of who is looking and who is seen emphasize ongoing colonial and neocolonial histories that continue to impact identity formations in Ireland. The possibilities and limitations of representing Afro-Irish self-determination arises as a site of contestation in Okorie's 2018 collection of three stories This Hostel Life. The second short story, “Under the Awning,” is a frame narrative that reclaims the liminal elements of second-person narration to assert emerging forms of Afro-Irish self-determination. This story exposes layers of racialization as it also indicates multiple possible voices materializing across multiple possible Irelands. In the seemingly disparate genres and media of documentary film and the short story, Seaview and This Hostel Life structurally challenge Irish racial formations that conform to a default colonial white norm. Reading these texts together exposes connections between postcolonial national identity and colonial racial formations that postcolonial nations willingly or unwillingly inherit through globalized economies and internationally integrated immigration reforms. By critically challenging racializing contexts and narratives during and after the Celtic Tiger, Seaview and This Hostel Life expand the representational possibilities for Afro-Irish self-determination in twenty-first century Irish literature and film.
Test Paper

We propose a novel method.
An appraisal of the practice of indigenous conflict resolution mechanisms in building a culture of peace in Bale zones, Oromia National Regional State, Ethiopia

This study examines the practice of indigenous conflict resolution mechanisms in building a culture of peace in Bale zones, Oromia National Regional State, Ethiopia. For the purposes of this study, qualitative research approaches accompanied by key informant interviews and focus group discussions have been employed. About 114 participants were participated in this study. The study was took place in 2020/2021. The findings of the study depicted that the causes of conflict in the study areas are dynamic. The study areas peoples used indigenous conflict resolution mechanisms to address dynamic causes of conflicts and build a culture of peace in post-conflict resolution. The study reveals that the efficacy of indigenous conflict resolution mechanisms in addressing complex conflict at grass root level contributed a lot in the process of restoring peace in post-conflict resolution. On the other hand, the finding shows that currently the efficacy of indigenous conflict resolution mechanisms in building a sustainable peace is not as effective as the past. Among the others, looking litigation as the only means to get truth, problems related with elders, brokers, religion, and attitudinal issues are some of obstacles that are deteriorating the effectiveness of indigenous conflict resolution mechanisms in building a culture of peace. The study suggests that there is an urgent comprehensive strategy to restore the effectiveness of indigenous conflict resolution mechanisms and cooperatively safeguarding them from deterioration and transfer to future generation with its nature, principles, norms, procedures, and implementation mechanisms.
Correlated Errors in Quantum Error Corrections

We show that errors are not generated correlatedly provided that quantum bits do not directly interact with (or couple to) each other. Generally, this no-qubits-interaction condition is assumed except for the case where two-qubit gate operation is being performed. In particular, the no-qubits-interaction condition is satisfied in the collective decoherence models. Thus, errors are not correlated in the collective decoherence. Consequently, we can say that current quantum error correcting codes which correct single-qubit-errors will work in most cases including the collective decoherence.
Applications of noisy quantum computing and quantum error mitigation to “adamantaneland”: a benchmarking study for quantum chemistry

Modeling isomers of C10H16 and carbocationic rearrangements of C10H15+ using the variational quantum eigensolver algorithm and quantum state tomography correction.
A Systematic Review of End-of-Life Care Communication Skills Training for Generalist Palliative Care Providers: Research Quality and Reporting Guidance

End-of-life care (EoLC) communication skills training for generalist palliative care providers is recommended in policy guidance globally. Although many training programs now exist, there has been no comprehensive evidence synthesis to inform future training delivery and evaluation.To identify and appraise how EoLC communication skills training interventions for generalist palliative care providers are developed, delivered, evaluated, and reported.Systematic review. Ten electronic databases (inception to December 2015) and five relevant journals (January 2004 to December 2015) were searched. Studies testing the effectiveness of EoLC communication skills training for generalists were included. Two independent authors assessed study quality. Descriptive statistics and narrative synthesis are used to summarize the findings.From 11,441 unique records, 170 reports were identified (157 published, 13 unpublished), representing 160 evaluation studies of 153 training interventions. Of published papers, eight were of low quality, 108 medium, and 41 high. Few interventions were developed with service user involvement (n = 7), and most were taught using a mixture of didactics (n = 123), reflection and discussion (n = 105), and role play (n = 86). Evaluation designs were weak: <30% were controlled, <15% randomized participants. Over half (n = 85) relied on staff self-reported outcomes to assess effectiveness, and 49% did not cite psychometrically validated measures. Key information (e.g., training duration, participant flow) was poorly reported.Despite a proliferation of EoLC communication skills training interventions in the literature, evidence is limited by poor reporting and weak methodology. Based on our findings, we present a CONSORT statement supplement to improve future reporting and encourage more rigorous testing.
Recalibrating the Correlation between Climate Change Mitigation Policy and Environmental Performance in Sub-Saharan Africa: Implications for Biosphere Resilience and Renewable Energy Transition

As the world transits from primitive sources of energy generation to renewable and sustainable energy, the impact of climate change and biosphere resilience to this innovative transition cannot be over-emphasized. The study analysed the correlation between Climate Change Mitigation Policy (CCMP) and Environmental Performance (EP) in Sub-Saharan Africa (SSA) using a linear regression statistical tool. The study leveraged integrative review and relied on secondary data. It found a positive correlation between CCMP and EP, indicating that focusing on climate change mitigation policies can enhance the SSA region's environmental performance (EP). The findings of this study posited that effective governance and strong institutional policies are crucial for implementing climate change mitigation policies, while, promoting sustainable development. The study concluded that implementing climate change mitigation policies effectively can positively affect the biosphere resilience, and drive the renewable energy transition in SubSaharan Africa. Furthermore, the findings offer noteworthy lessons for policymakers and practitioners working to address the challenges of climate change, environmental degradation, and energy poverty in SSA.
sj-pdf-3-wjn-10.1177_01939459221114079 – Supplemental material for Nurse Managers’ Leadership, Patient Safety, and Quality of Care: A Systematic Review

Supplemental material, sj-pdf-3-wjn-10.1177_01939459221114079 for Nurse Managers’ Leadership, Patient Safety, and Quality of Care: A Systematic Review by Seung Eun Lee, Lee Hyunjie and Somin Sang in Western Journal of Nursing Research
Multi-Modal Interpretability for Enhanced Localization in Vision-Language Models

Recent advances in vision-language models have significantly expanded the frontiers of automated image analysis. However, applying these models in safety-critical contexts remains challenging due to the complex relationships between objects, subtle visual cues, and the heightened demand for transparency and reliability. This paper presents the Multi-Modal Explainable Learning (MMEL) framework, designed to enhance the interpretability of vision-language models while maintaining high performance. Building upon prior work in gradient-based explanations for transformer architectures (Grad-eclip), MMEL introduces a novel Hierarchical Semantic Relationship Module that enhances model interpretability through multi-scale feature processing, adaptive attention weighting, and cross-modal alignment. Our approach processes features at multiple semantic levels to capture relationships between image regions at different granularities, applying learnable layer-specific weights to balance contributions across the model's depth. This results in more comprehensive visual explanations that highlight both primary objects and their contextual relationships with improved precision. Through extensive experiments on standard datasets, we demonstrate that by incorporating semantic relationship information into gradient-based attribution maps, MMEL produces more focused and contextually aware visualizations that better reflect how vision-language models process complex scenes. The MMEL framework generalizes across various domains, offering valuable insights into model decisions for applications requiring high interpretability and reliability.
The Hidden Shadows of social media: Cyberbullying and Its Impact on Adolescent Mental Health

With the development of social media, cyberbullying has become a new form of bullying behavior that poses a great threat to adolescents' mental health. This study focuses on the relationship between social media and cyberbullying, and reveals the negative effects of cyberbullying on mental health, such as leading to anxiety, depression, or social isolation among adolescents, through different survey data, as well as analyzing the help of social media characteristics on cyberbullying behavior.This study was conducted by selecting 11 existing literature online, focusing on peer-reviewed articles and previous studies on cyberbullying and adolescent mental health. Survey data and qualitative interviews from other studies were analyzed to explore the relationship between social media and bullying behavior, focusing on the role of anonymity and information dissemination in aiding cyberbullying.The anonymity and high dissemination rate characteristics of social media increase the frequency and unknown nature of bullying behavior. Females and economically disadvantaged groups are more vulnerable to cyberbullying. In addition there are obvious deficiencies in the existing laws and policies to deal with cyberbullying. Cyberbullying has a serious impact on adolescents' mental health. Effective interventions, including digital ethics education, parental involvement, and strengthened legal measures, are essential to reduce cyberbullying and protect adolescents' mental and physical health.
Weight Dependence of Local Exchange-Correlation Functionals in Ensemble Density-Functional Theory: Double Excitations in Two-Electron Systems

Gross--Oliveira--Kohn (GOK) ensemble density-functional theory (GOK-DFT) is a time-\textit{independent} extension of density-functional theory (DFT) which allows to compute excited-state energies via the derivatives of the ensemble energy with respect to the ensemble weights. Contrary to the time-dependent version of DFT (TD-DFT), double excitations can be easily computed within GOK-DFT. However, to take full advantage of this formalism, one must have access to a \textit{weight-dependent} exchange-correlation functional in order to model the infamous ensemble derivative contribution to the excitation energies. In the present article, we discuss the construction of first-rung (i.e., local) weight-dependent exchange-correlation density-functional approximations for two-electron atomic and molecular systems (He and H$_2$) specifically designed for the computation of double excitations within GOK-DFT. In the spirit of optimally-tuned range-separated hybrid functionals, a two-step system-dependent procedure is proposed to obtain accurate energies associated with double excitations.
Retraction of ‘An Empirical Study of an Internet Marketing Strategy for Search Engine Optimization. Human Factors and Ergonomics in Manufacturing &amp; Service Industries, 23, 528–540. doi: 10.1002/hfm.20348

The article listed above, published online on Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editors‐in‐Chief, Gavriel Salvendy and Waldemar Karwowski, and Wiley Periodicals, Inc. The retraction has been agreed due to evidence indicating that the peer review of this paper was compromised. It is believed that the paper was accepted based on recommendations from reviewers with conflicts of interest. In addition, ISI provided the publisher with evidence of inappropriate manipulation of citations.
Atom: Neural Traffic Compression with Spatio-Temporal Graph Neural Networks

Storing network traffic data is key to efficient network management; however, it is becoming more challenging and costly due to the ever-increasing data transmission rates, traffic volumes, and connected devices. In this paper, we explore the use of neural architectures for network traffic compression. Specifically, we consider a network scenario with multiple measurement points in a network topology. Such measurements can be interpreted as multiple time series that exhibit spatial and temporal correlations induced by network topology, routing, or user behavior. We present \textit{Atom}, a neural traffic compression method that leverages spatial and temporal correlations present in network traffic. \textit{Atom} implements a customized spatio-temporal graph neural network design that effectively exploits both types of correlations simultaneously. The experimental results show that \textit{Atom} can outperform GZIP's compression ratios by 50\%-65\% on three real-world networks.
Alpha MAML: Adaptive Model-Agnostic Meta-Learning

Model-agnostic meta-learning (MAML) is a meta-learning technique to train a model on a multitude of learning tasks in a way that primes the model for few-shot learning of new tasks. The MAML algorithm performs well on few-shot learning problems in classification, regression, and fine-tuning of policy gradients in reinforcement learning, but comes with the need for costly hyperparameter tuning for training stability. We address this shortcoming by introducing an extension to MAML, called Alpha MAML, to incorporate an online hyperparameter adaptation scheme that eliminates the need to tune meta-learning and learning rates. Our results with the Omniglot database demonstrate a substantial reduction in the need to tune MAML training hyperparameters and improvement to training stability with less sensitivity to hyperparameter choice.
Developing an objectives hierarchy for multicriteria decisions on land use options, with a case study of biodiversity conservation and forestry production from Papua, Indonesia

A framework was developed for the construction of an objectives hierarchy for multicriteria decisions in land use planning. The process began through identification of fundamental objectives; these were iteratively decomposed into a hierarchy of subobjectives until a level was reached at which subobjectives had measurable attributes. Values were derived for attributes through a variety of methods and weights assigned to objectives through preference elicitation. The framework assumed that the objectives could be incorporated into a linear value function; this required attributes to satisfy preference and difference independence conditions. Strategies were developed to address typical features that distinguish land use decisions from many other multicriteria decisions. The methodology was illustrated with a case study of land use planning in a forestry concession in the Merauke region of Papua Province, Indonesia. The problem involved severe hard constraints; the analysis showed how these can be accommodated within the framework. Results integrated interests and preferences of a diverse set of stakeholders (resident peoples, developers, and conservation professionals) and were intended for implementation. This methodology is extendible to other land use problems.
Average transverse momenta of baryon production at p-p collider experiments and their crucial implications for the high energy hadroproduction physics

The phenomenological approach in the framework of Quark-Gluon String Model (QGSM) has been applied to the description of transverse momentum spectra for the baryon production at colliders. The analysis of data on hyperon transverse momentum distributions,dN/dp_t, demonstrates a difference in the dynamics of multiparticle production in proton-proton vs. antiproton-proton collisions in the region of low p_t . The most important contribution in antip-p reaction goes from fragmentation of antidiquark-diquark side of pomeron diagram. The complete study of the energy dependence of average transverse momenta for the energies from sqrt(s)= 0.2 to 7. TeV shows the slight growing of with energy. No dramatic changes were seen on the range from Tevatron to LHC, which may be responsible for "knee" in the cosmic ray proton spectra. The average transverse momentum analysis through the different mass of hadrons reveals some regularity in the mass gaps between the hadron generations. This observation suggests that more hadrons with the following masses 13.7, 37.3, 101.5, 276, 750 ... GeV are expected by geometrical progression with the mass factor of order $δ{lnM}$=1 . These states may possess new quantum numbers beyond the Standard Model. The possibility of QGSM to construct the spectra of baryons in the whole range of x_F gives obvious advantages in the description of production asymmetries: the baryon-over-antibaryon access in the central region of proton-proton collisions, the baryon-to-meson abnormal ratios in nucleus-nucleus reactions, the growing ratios of secondary particles in cosmic ray spectra as well as the recently observed negative asymmetry for charmed baryon/antibaryon spectra at the far rapidity point Y=2 in LHCb experiment. This study, based on the routine analysis of collider data, has many crucial implications for the entire field of hadroproduction physics.
The influence of adverse events on the quality of nursing care and patients’ safety

Introduction : High quality of medical services is essential to proper healthcare functioning and to achieve aims. High quality of nursing care should have the same characteristics as the whole healthcare system. Although current healthcare systems focus on best quality medical services, the number of adverse events is increasing. It sometimes happens that a patient suffers injuries not due to his/her illness, but because of poorly organised healthcare. Aim of the research : To assess the influence of adverse events and their identification on nursing care quality and to analyse the correlation between patient safety and adverse events identification and reporting. Material and methods: The research was conducted in hospital wards that have and do not have a Certificate of Quality Management System. In the research, the Hospital Survey on Patient Culture prepared by the Agency for Healthcare Research and Quality was used as well as the author’s own survey. Results: In the survey, nurses’ activities were evaluated in the context of adverse events identification. As the most common undesirable events, the following were considered: discrepancy connected with organisation and administration (35%), medical equipment (24%), hospital infections (23%), medication administration (22%), doctor’s (20%) and nurse’s (19%) activity, and blood and blood related specimen transfusion (10%). However, these areas were not disastrous. Conclusions: It has been stated that nurses, for fear of disciplinary consequences, are more unwilling to report such events. Therefore, it is essential to introduce legal regulations.
Universally Sloppy Parameter Sensitivities in Systems Biology

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring \emph{in vivo} biochemical parameters is difficult, and collectively fitting them to other data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a `sloppy' spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.