ethicalabs/Research-Intent-Collab huggingface dataset:
Capturing quality of life in pouch anal and vaginal fistula: Development of PAVF-QoL-14, a patient-reported outcome measure

Abstract                 Introduction  Perianal pouch fistula can significantly affect quality of life, yet no disease-specific patient reported outcome measure (PROM) exists. We have developed and validated a 14-item PROM - the Pouch Anal and Vaginal Fistula Quality of Life scale (PAVF-QoL-14). Methods  COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guidance for PROM development was used to develop and validate PAVF-QoL-14.  A systematic literature review and semi-structured patient interviews (n = 14) identified key domains. Cognitive interviews and item-level content validity index with experts refined the draft questionnaire. Psychometric evaluation included principal component analysis (PCA), internal consistency testing, and construct validity assessment against Hospital Anxiety and Depression Scale (HADS) and Short-Form 12 (SF-12). Test-rest analysis was performed on 76 patients. Results  An initial 34-item draft scale was generated and refined through cognitive interviews (n = 10) and psychometric testing (n = 76). Flesch readability score was 63%. Kaiser-Meyer-Olkin test confirmed sampling adequacy (KMO = 0.905), and correlations between items were found significant using Bartlett’s test of sphericity (p &lt; 0.001). Four domains (symptoms, discharge, faecal incontinence, and future concerns) were extracted, explaining 63.7% of the total variance. Following stepwise regression, a 14-item short-form was developed, demonstrating excellent internal consistency (Cronbach’s α = 0.920). Responsiveness and stability were robust. Construct validity was excellent as PAVF-QoL-14 exhibited strong correlations with HADS (r = 0.589, p &lt; 0.001) and SF-12 (r = 0.525, p &lt; 0.001). Conclusion  PAVF-QoL-14 provides a concise, validated, and disease-specific measure of quality of life for pouch-related fistula, ready for use in clinical practice and trials.
In Search of A ‘Just’ World: The Permanent Peoples’ Tribunal and The Challenge to International Criminal Law&lt;i&gt;&lt;/i&gt;

International criminal law presents itself as the main global response to atrocity, yet its selective prosecutions, narrow construction of victimhood and focus on individual perpetrators leave structural injustice largely untouched. This article argues that this doctrinal and institutional focus produces a form of structural impunity, particularly in relation to harms suffered by migrants. It develops this claim through a close reading of the Permanent Peoples’ Tribunal’s (PPT) 2017–2020 sessions on the rights of migrants and refugee peoples. Using a doctrinal and critical-interpretive method, the article analyses the Tribunal’s legal basis in the law of peoples, its construction of migrants as victims of systemic injustice, and its articulation of ‘system crimes’ that are rooted in economic, political and legal structures rather than isolated acts. The article shows how the PPT attributes responsibility to European states and institutions for a migration regime that predictably produces deaths at sea, abuses in detention and degrading living conditions. It argues that the Tribunal advances a model of corrective distributive justice that links accountability to structural repair and redistribution. The conclusion suggests that a credible international justice project must move beyond retributive trials to confront the global structures that sustain violence and inequality.
Na-Ion Battery Anodes: Materials and Electrochemistry

The intermittent nature of renewable energy sources, such as solar and wind, calls for sustainable electrical energy storage (EES) technologies for stationary applications. Li will be simply too rare for Li-ion batteries (LIBs) to be used for large-scale storage purposes. In contrast, Na-ion batteries (NIBs) are highly promising to meet the demand of grid-level storage because Na is truly earth abundant and ubiquitous around the globe. Furthermore, NIBs share a similar rocking-chair operation mechanism with LIBs, which potentially provides high reversibility and long cycling life. It would be most efficient to transfer knowledge learned on LIBs during the last three decades to the development of NIBs. Following this logic, rapid progress has been made in NIB cathode materials, where layered metal oxides and polyanionic compounds exhibit encouraging results. On the anode side, pure graphite as the standard anode for LIBs can only form NaC64 in NIBs if solvent co-intercalation does not occur due to the unfavorable thermodynamics. In fact, it was the utilization of a carbon anode in LIBs that enabled the commercial successes. Anodes of metal-ion batteries determine key characteristics, such as safety and cycling life; thus, it is indispensable to identify suitable anode materials for NIBs. In this Account, we review recent development on anode materials for NIBs. Due to the limited space, we will mainly discuss carbon-based and alloy-based anodes and highlight progress made in our groups in this field. We first present what is known about the failure mechanism of graphite anode in NIBs. We then go on to discuss studies on hard carbon anodes, alloy-type anodes, and organic anodes. Especially, the multiple functions of natural cellulose that is used as a low-cost carbon precursor for mass production and as a soft substrate for tin anodes are highlighted. The strategies of minimizing the surface area of carbon anodes for improving the first-cycle Coulombic efficiency are also outlined, where graphene oxide was employed as dehydration agent and 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) was used to unzip wood fiber. Furthermore, surface modification by atomic layer deposition technology is introduced, where we discover that a thin layer of Al2O3 can function to encapsulate Sn nanoparticles, leading to a much enhanced cycling performance. We also highlight recent work about the phosphorene/graphene anode, which outperformed other anodes in terms of capacity. The aromatic organic anode is also studied as anode with very high initial sodiation capacity. Furthermore, electrochemical intercalation of Na ions into reduced graphene oxide is applied for fabricating transparent conductors, demonstrating the great feasibility of Na ion intercalation for optical applications.
A Knowledge-Guided Temporal Graph Neural Network for Predicting Rate of Penetration in Complex Formations

Summary                   Accurate rate of penetration (ROP) prediction is essential for optimizing drilling performance and reducing operational costs. However, the complexity and uncertainty inherent in drilling operations pose significant challenges to existing data-driven models, limiting their capacity to generalize across diverse conditions and effectively incorporate domain knowledge. In this paper, we propose a knowledge-guided hybrid temporal graph neural network (KHTGNN) for robust ROP prediction. First, explicit domain knowledge is applied to perform physical corrections on drilling parameters during feature engineering, enhancing data quality. Second, an adaptive graph construction method based on node embedding is introduced to dynamically model the evolving correlations among drilling parameters. Third, a hybrid temporal graph neural network (GNN) is designed to capture both intravariable and intervariable dependencies. Moreover, domain-specific rock-breaking mechanism equations are embedded as soft constraints within the model’s loss function to enforce physical consistency. To further enhance generalization, a multiple kernel (MK) maximum mean discrepancy (MMD) approach is integrated to achieve domain-adaptive learning across different wells. The results demonstrate that KHTGNN outperforms current models, achieving a mean absolute percentage error (MAPE) of 9.49%, a mean absolute error (MAE) of 1.64 m/h, and a coefficient of determination (R2) of 0.99. Ablation studies validate the contributions of physical data correction, knowledge constraints, and domain adaptation, emphasizing the critical role of domain knowledge integration in improving predictive performance. This work provides a robust knowledge-guided framework for sequential parameter prediction tasks in complex industrial systems.
Business ethics and corporate social responsibility

A textbook covering all areas of ethics and responsibility in business. The book is international in focus, and covers not only managerial decision making in this area but also the over-arching structures and frameworks within which managers make choices relating to ethics.
Topological Signal Processing Over Cell MultiComplexes Via Cross-Laplacian Operators

One of the key challenges in many research fields is uncovering how different interconnected systems interact within complex networks, typically represented as multi-layer networks. Capturing the intra- and cross-layer interactions among different domains for analysis and processing calls for topological algebraic descriptors capable of localizing the homologies of different domains, at different scales, according to the learning task. Our first contribution in this paper is to introduce the Cell MultiComplexes (CMCs), which are novel topological spaces that enable the representation of higher-order interactions among interconnected cell complexes. We introduce cross-Laplacian operators as powerful algebraic descriptors of CMC spaces able to capture different topological invariants, whether global or local, at different resolutions. Using the eigenvectors of these operators as bases for the signal representation, we develop topological signal processing tools for signals defined over CMCs. Then, we focus on the signal spectral representation and on the filtering of noisy flows observed over the cross-edges between different layers of CMCs. We show that a local signal representation based on cross-Laplacians yields a better sparsity/accuracy trade-off compared to monocomplex representations, which provide overcomplete representation of local signals. Finally, we illustrate a topology learning strategy designed to infer second-order cross-cells between layers, with applications to brain networks for encoding inter-module connectivity patterns.
Harvesting System for Autonomous Robotic in Agriculture: A Review.

Technology in the modern day has led to the development of agricultural robots that helps to increase the agriculture productivity. Numerous research has been conducted to help increasing the capability of the robot in assisting agricultural operation, which leads to development of autonomous robot. The development aim is to help reducing agricultures dependency on operators, workers, also reducing the inaccuracy caused by human errors. There are two important development components for autonomous harvesting. The first component is Machine vision for detecting the crops and guiding the robot through the field and the second component actuator to grab or picking the crops or fruits.
A Study on Crowdsourcing for Multi-Label Affect Annotation

(主査) 准教授 小山 聡, 教授 栗原 正仁, 教授 山本 雅人, 教授 小野 哲雄, 教授 川村 秀憲 情報科学研究科（複合情報学専攻）
Causal inference via algebraic geometry: feasibility tests for functional causal structures with two binary observed variables

We provide a scheme for inferring causal relations from uncontrolled statistical data based on tools from computational algebraic geometry, in particular, the computation of Groebner bases. We focus on causal structures containing just two observed variables, each of which is binary. We consider the consequences of imposing different restrictions on the number and cardinality of latent variables and of assuming different functional dependences of the observed variables on the latent ones (in particular, the noise need not be additive). We provide an inductive scheme for classifying functional causal structures into distinct observational equivalence classes. For each observational equivalence class, we provide a procedure for deriving constraints on the joint distribution that are necessary and sufficient conditions for it to arise from a model in that class. We also demonstrate how this sort of approach provides a means of determining which causal parameters are identifiable and how to solve for these. Prospects for expanding the scope of our scheme, in particular to the problem of quantum causal inference, are also discussed.
Reducing Cross-Border Transaction Fees: The Cost-SavingPotential of Central Bank Digital Currencies

High international transaction fees remain a significant barrier in international corporate finance, primary due to inefficiencies in traditional cross-border payment methods like correspondent banking. This essay evaluates the potential of Central Bank Digital Currencies (CBDCs) to reduce international transaction costs compared to conventional payment systems. Asemi-systematic literature review was conducted, analysing empirical data from recent pilotstudies, academic research, and institutional reports. Results indicate that CBDCs substantially reduce intermediary involvement, currency conversion fees, and settlement times, leading to cost efficiencies. Specifically, CBDC platforms streamline transaction processes by minimizing correspondent bank fees, providing more competitive and transparent foreign exchange rates, and achieving near-instant settlement times. The findings suggest significant cost-saving potential under optimal conditions, although these savings depend heavily on international regulatory coordination, technical interoperability, and effective governance structures. The study concludes that while CBDCs hold considerable promise for reducing cross-border payment costs, achieving these benefits requires overcoming substantial institutional and operational challenges.
Primordial Magnetic Fields that Last?

The magnetic fields we observe in galaxies today may have their origins in the very early universe. While a number of mechanisms have been proposed which lead to an appreciable field amplitude at early times, the subsequent evolution of the field is of crucial importance, especially whether the correlation length of the field can grow as large as the size of a protogalaxy. This talk is a report on work in progress, in which we consider the fate of one specific primordial field scenario, driven by pseudoscalar effects near the electroweak phase transition. We argue that such a scenario has a number of attractive features, although it is still uncertain whether a field of appropriate size can survive until late times.
Reef fishes biodiversity and conservation at the largest Brazilian coastal Marine Protected Area (MPA Costa dos Corais)

Abstract Coral reefs harbor one of the largest fish biodiversity on earth; yet information on reef fishes is still absent for many regions. We analyzed reef fish richness, distribution, and conservation on the largest Brazilian multiple use coastal MPA; which cover a large extent of coral reefs at the SWA. A total of 325 fish species have been listed for MPA Costa dos Corais, including Chondrichthyes (28 species) and Actinopterygii (297). Fish species were represented by 81 families and the most representative families were Carangidae (23 species), Labridae (21) and Gobiidae (15). The MPA fish richness represented 44% of all recorded fish species of the Southwestern Atlantic Ocean (SWA) highlighting the large-scale importance of this MPA. A total of 40 species (12%) are registered at Near Threatened (NT), Vulnerable (VU), Endangered (EN) or Critically Endangered (CR). This study reinforces the importance of MPA Costa dos Corais on reef fish biodiversity and conservation and emphasize the urgent need of conservation strategies.
An optimal experimental design approach to sensor placement in continuous stochastic filtering

Abstract                                        Sequential filtering and spatial inverse problems assimilate data points distributed either temporally (in the case of filtering) or spatially (in the case of spatial inverse problems). Sometimes it is possible to choose the position of these data points (which we call sensors here) in advance, with the goal of maximising the expected information gain (or a different metric of performance) from future data, and this leads to an Optimal Experimental Design (OED) problem. Here we revisit an interpretation of optimising sensor placement as an integration with respect to a general probability measure                                                                     $$\xi $$                                                    ξ                                                                                          . This generalises the problem of discrete-time sensor placement (which corresponds to the special case where the probability measure is a mixture of Diracs) to an infinite-dimensional, but mathematically more well-behaved setting. We focus on the continuous-time stochastic filtering setting, whose solution is governed by the Zakai equation. We derive an expression for the Fréchet derivative of a general OED utility functional, the key to which is an adjoint (backwards in time) differential equation. This paves the way for utilising new gradient-based methods for solving the corresponding optimisation problem, as a potentially more efficient alternative to (semi-)discrete optimisation methods, e.g. based on greedy insertion and deletion of sensor placements.
About the connection between the $C_{\ell}$ power spectrum of the Cosmic Microwave Background and the $Γ_{m}$ Fourier spectrum of rings on the sky

8 pages, 8 figures
Mixing times for two classes of stochastically modeled reaction networks

The past few decades have seen robust research on questions regarding the existence, form, and properties of stationary distributions of stochastically modeled reaction networks. When a stochastic model admits a stationary distribution an important practical question is: what is the rate of convergence of the distribution of the process to the stationary distribution? With the exception of \cite{XuHansenWiuf2022} pertaining to models whose state space is restricted to the non-negative integers, there has been a notable lack of results related to this rate of convergence in the reaction network literature. This paper begins the process of filling that hole in our understanding. In this paper, we characterize this rate of convergence, via the mixing times of the processes, for two classes of stochastically modeled reaction networks. Specifically, by applying a Foster-Lyapunov criteria we establish exponential ergodicity for two classes of reaction networks introduced in \cite{anderson2018some}. Moreover, we show that for one of the classes the convergence is uniform over the initial state.
CORPORATE SOCIAL RESPONSIBILITY AND BUSINESS ETHICS

Corporate Social Responsibility (CSR) and Business Ethics have become essential components of strategic management, reflecting the growing demand for organizations to operate with accountability, transparency, and a sense of purpose beyond profit. This chapter explores the concepts, principles, and practices that define responsible corporate behavior, emphasizing the ethical obligations businesses have toward various stakeholders including employees, customers, communities, and the environment. It examines how ethical frameworks guide decision-making and how CSR initiatives can enhance brand reputation, stakeholder trust, and long-term sustainability. The chapter also discusses the integration of CSR and ethics into corporate strategy, illustrating how businesses can align social responsibility with competitive advantage. Topics such as ethical leadership, corporate governance, environmental stewardship, and social innovation are addressed through realworld examples and global case studies. Ultimately, this chapter encourages readers to view CSR and business ethics not just as compliance measures, but as strategic imperatives for building resilient, sociallyconscious, and future-ready organizations.
Heliospheric modulation of galactic cosmic rays: Effective energy of ground-based detectors

Variability of Galactic cosmic ray (GCR) is often expressed in terms of the modulation potential, which is typically assessed using energy-integrating ground-based detectors, such as neutron monitors (NMs) for the last decades or cosmogenic isotopes on the time scales of centuries and millennia.  In order to estimate the energy dependence of the GCR variability we re-assess here the effective energy $E_{\rm eff}$ of each type of detector, which is defined so that the variability of the GCR particles at this energy is equal to that of the detector's count rate.  We found that $E_{\rm eff}$ is 11--12 GeV/nuc for the standard polar sea-level neutron monitor, but it is essentially smaller for cosmogenic isotopes, being 6--7 GeV/nuc for $^{14}$C and 5.5--6 GeV/nuc for $^{10}$Be, respectively.  It is also discussed that this effective energy is robustly defined and is hardly dependent on the primary assumptions on the local interstellar spectrum of GCR.
Effect of aberration on partial-sky measurements of the cosmic microwave background temperature power spectrum

14 pages, 8 figures. (v2) Including three more masks used for Planck analysis (lensing mask, HFI power spectrum mask, HFI Gal040 mask), and discussion about the effect of aberration on estimation of cosmological parameters such as angular diameter distance to the last-scattering surface, Hubble parameter and dark-energy equation of state
Social and Ecological Synergy: Local Rulemaking, Forest Livelihoods, and Biodiversity Conservation

Participation in tropical forest governance by local people results in positive outcomes for conservation and subsistence.
The demand for safe liquid assets and the implications of issuing a Central Bank Digital Currency for bank funding instruments

The pros and cons of issuing a Central Bank Digital Currency (CBDC) is currently debated by Norges Bank and other central banks. A CBDC would grant access to the central bank balance sheet to a broader set of economic agents, including for example companies or individuals. How such access would be designed or administered are topics of the discussion. One dimension to consider is the potential impact on the stability of the financial system through the effect of CBDC issuance on bank funding markets. This article provides an overview on research related to the demand for financial institutions’ funding instruments and derives implications for the issuance of a CBDC. A key message is that CBDC has the potential to substantially crowd out bank funding instruments due to its superior safety features.
World Trade Organization: Rules of Conduct for the Understanding on Rules and Procedures Concerning the Settlement of Disputes

Each person covered by these Rules (as defined in paragraph 1 of Section IV below and hereinafter called “covered person”) shall be independent and impartial, shall avoid direct or indirect conflicts of interest and shall respect the confidentiality of proceedings of bodies pursuant to the dispute settlement mechanism, so that through the observance of such standards of conduct the integrity and impartiality of that mechanism are preserved. These Rules shall in no way modify the rights and obligations of Members under the DSU nor the rules and procedures therein.