ethicalabs/Research-Intent-Collab huggingface dataset:
Trace element and isotope Geochemistry of Neoarchean carbonate rocks from the Dharwar craton, southern India: Implications for depositional environments and mantle influence on ocean chemistry

Abstract   Neoarchean carbonate rocks of the Vanivilas Formation (2.7 Ga) occur extensively in greenstone belts of western Dharwar craton, are associated with banded Fe-Mn formations and clastic sediments including diamictites, preserve well-developed stromatolitic structures. We intend to understand the depositional environments of these carbonates, extent of oxygenation in shallow oceans and to examine the mantle and continent inputs to Neoarchean oceans. Depleted LREESN and slightly enriched HREESN patterns, Y/Ho > 28, La, Y and Eu spiking and varying Ce anomalies shown by most of the samples, are consistent with their marine origin. However, 4 samples exhibit negative Ce anomaly indicating presence of oxygen supporting the hypotheses of localised, protected, shallow marine oxygenation in redox stratified late Meso- to Neoarchean oceans. δ13C values are well preserved (mean = -0.27‰ (PDB)) similar to other Archean marine carbonates from other cratons and show no correlation with δ18O and Mn/Sr ratios. Whereas, the δ18O values (mean= -10.78‰) show considerable depletion and can be attributed to later interactions with diagenetic/meteoric fluids. The mantle dominated, yet continental affected Neoarchean ocean chemistry is apparent from Sr-Nd isotope systematics. The lowest 87Sr/86Sri of carbonates, 0.7024 reflects ocean water Sr isotopic composition at 2.7 Ga, is higher than the model seawater evolution curve of  Shields and Veizer, (2002) . Similarly, other recent studies on Archean carbonates and barites reported higher 87Sr/86Sri values. This is due to the existence of Paleoarchean continental crust subjected to chemical weathering resulting in increased continental flux than previously thought of. Range of ℇNd values (-8.39 to 5.83) suggest that the carbonates had variable contributions of Nd from a long term depleted mantle through hydrothermal fluids, as well as, from 3.5 Ga old continental crust in the Dharwar craton. The carbonates were deposited in the Neoarchean ocean at variable depths within the shelf and those deposited at shallower and deeper environments are characterized respectively, by inputs derived from chemical weathering of ≥3.5 Ga old continental crust and mantle through hydrothermal fluids associated with submarine volcanic activity.
Protection of Minorities' culture and cultural rights under the Light of CESCR's General Comment NO.21

Cultural Rights (CRs) are the most non-developed rights among human rights in the terms of normative content, the scope of implementation and legal enforceability. In this regard, the right of minorities and persons belonging to these groups to participate in their own life has been affected and neglected more seriously. On 21 December 2009, the Committee on Economic, Social and Cultural Rights (CESCRs) adopted General Comment No. 21 on the right of everyone to take part in cultural life that could be accounted as a reference point in the protection of culture and cultural rights of minorities. In this Comment, the CESCRs gives solid substance to the norm through clearly defining its content and scope, the beneficiaries and the nature of the right, and the range of obligations it imposes on State Parties for its implementation; as such it could serve as a potential pillar for the protection, preservation, and promotion of minorities' culture, and consequently, CRs. The present study aims to investigate the achievements of General Comment No. 21 of CESCRs for the protection of culture and cultural rights of minorities.
Kasteran* — Memory Calculus: Linear Type System — Compiler, Programming Languages, Type Theory, Sovereign AI, and Post-Cloud Architecture (Kasteran)

Kasteran* uses **linear types** to manage memory. Every value is tracked by the compiler and must be consumed exactly once. This eliminates garbage collection, use-after-free errors, and data races at compile time.    Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores compiler, programming languages in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
Participatory Early Warning Systems: Youth, Citizen Science, and Intergenerational Dialogues on Disaster Risk Reduction in Brazil

Abstract Building national people-centered early warning systems (EWS) is strongly recommended by the United Nations International Strategy for Disaster Reduction (UNISDR). Most of the scientific literature is critical of the conventional view of EWS as a linear model with a top-down approach, in which technological features are given more attention than human factors. It is argued that EWS should be people-centered, and used for risk prevention, with an emphasis on resilience, rather than only being triggered when a hazard occurs. However, both the UNISDR and the literature fail to say how a people-centered EWS should be built, and what steps are needed to put EWS into effect. This article examines the obstacles and measures required to promote people-centered EWS, with a focus on the situation in Brazil. After assessing the institutional vulnerability of EWS, we analyze some measures that can be taken to reduce institutional vulnerability, based on experiences with a participatory citizen science educational project that involved high school students. Some guidelines are developed for adopting a bottom-up approach towards achieving the four elements of EWS—risk knowledge, monitoring, communication of warnings, and response capability—with the help of school curricula.
Identifying the Right Policies for Increasing the Efficiency of the Renewable Energy Transition with a Novel Fuzzy Decision-Making Model

Necessary improvements should be made to the determinants of renewable energy transition. However, it is necessary to give priority to the issues that are more important while making improvements to this process since all improvements cause cost increase. Therefore, a new analysis is needed in which the most important ones among these criteria will be determined. The purpose of this study is to identify the most essential items for renewable energy transition. Within this context, five criteria are selected based on the literature review results. Spherical fuzzy (TOPSIS-based DEMATEL) TOP-DEMATEL methodology is taken into consideration to calculate the weights of these indicators. In the second part of the study, alternatives are ranked with Spherical fuzzy ranking technique by geometric mean of similarity ratio to optimal solution (RATGOS). In this context, BRICS countries (Brazil, Russia, India, China, South Africa) are selected as alternatives. The main contribution is that a new method (RATGOS) is created while considering geometric mean in proportional concepts. On the other side, a new methodology (TOP-DEMATEL) is also proposed to overcome criticisms in DEMATEL. It is concluded that technological development plays the most important role for the success of renewable energy transition. Similarly, finding effective financial source is also very important in this condition. The ranking results also demonstrate that China and Russia are the most successful countries regarding renewable energy transition. However, it is also defined that South Africa and India are less successful in renewable energy transition in comparing with other BRICS countries. It is understood that technological development plays a critical role in increasing the efficiency of the renewable energy transition process. Thanks to the use of up-to-date technology, it is possible to use energy resources more efficiently. Technological developments are also necessary for the efficiency of energy storage processes. Variations in climatic conditions cause irregularities in the energy production process. Thanks to the efficient energy storage processes, it is possible to solve this problem.
Weather Forecasting Using Artificial Neural Network

Accurate weather forecast plays a vital role in today's world as agricultural and indusrial sectors are principally dependent on weather conditions. It is also used to forecast and warm about natural disasters. Weather forecasting is determination of the right values of weather parameters and furhermore the future weather condition based on these parameters. In this study different weather parameters were collected from national climate data center then using Long-short term memory(LSTM) technique, the neural network is trained for different combinations. In prediction of future weather condition using LSTM the neural network is trained using different combinations of weather parameters, the weather parameters used are temperature, precipitation, wind speed. pressure, dew point visibility and humidity. After training of LSTM model using these parameters the prediction of future weather is done.
OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep Learning

7 pages, 7 figures, 4 tables
The human rights to water and sanitation

No
Jump Type Stochastic Differential Equations with Non-Lipschitz Coefficients: Non Confluence, Feller and Strong Feller Properties, and Exponential Ergodicity

This paper considers multidimensional jump type stochastic differential equations with super linear growth and non-Lipschitz coefficients. After establishing a sufficient condition for nonexplosion, this paper presents sufficient non-Lipschitz conditions for pathwise uniqueness. The non confluence property for solutions is investigated. Feller and strong Feller properties under non-Lipschitz conditions are investigated via the coupling method. Sufficient conditions for irreducibility and exponential ergodicity are derived. As applications, this paper also studies multidimensional stochastic differential equations driven by Lévy processes and presents a Feynman-Kac formula for Lévy type operators.
The Value of Extracting Clinician-Recorded Affect for Advancing Clinical Research on Depression: Proof-of-Concept Study Applying Natural Language Processing to Electronic Health Records (Preprint)

BACKGROUND                         Affective characteristics are associated with depression severity, course, and prognosis. Patients’ affect captured by clinicians during sessions may provide a rich source of information that more naturally aligns with the depression course and patient-desired depression outcomes.                                                                       OBJECTIVE                         In this paper, we propose an information extraction vocabulary used to pilot the feasibility and reliability of identifying clinician-recorded patient affective states in clinical notes from electronic health records.                                                                       METHODS                         Affect and mood were annotated in 147 clinical notes of 109 patients by 2 independent coders across 3 pilots. Intercoder discrepancies were settled by a third coder. This reference annotation set was used to test a proof-of-concept natural language processing (NLP) system using a named entity recognition approach.                                                                       RESULTS                         Concepts were frequently addressed in templated format and free text in clinical notes. Annotated data demonstrated that affective characteristics were identified in 87.8% (129/147) of the notes, while mood was identified in 97.3% (143/147) of the notes. The intercoder reliability was consistently good across the pilots (interannotator agreement [IAA] &amp;gt;70%). The final NLP system showed good reliability with the final reference annotation set (mood IAA=85.8%; affect IAA=80.9%).                                                                       CONCLUSIONS                         Affect and mood can be reliably identified in clinician reports and are good targets for NLP. We discuss several next steps to expand on this proof of concept and the value of this research for depression clinical research.
A simple estimator for discrete-time samples from affine stochastic delay differential equations

zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Assessing Rwexit: the impact and implications of Rwanda’s withdrawal of its article 34(6)-declaration before the African Court on Human and Peoples’ Rights

ABSTRACT: This article reviews and analyses Rwanda’s withdrawal of the declaration that allows individuals and NGOs direct access to the African Court of Human and Peoples’ Rights, pursuant to article 34(6) of the African Court Protocol, which is a first in the young life of the preventing those accused of genocide minimisation or denial from accessing the African Court, thus seemingly attempting to deny certain Rwandans an avenue to assert their rights. The article further argues that, faced with the first prominent challenge to its authority, the African Court produced a wellreasoned decision that allows withdrawal but only after a 12-month cooling off period. What is of more concern is what appears to be a six-month delay in rendering the publicly available decision, which is unfortunate especially in the context of an envisaged 12-month cooling-off period. The article concludes by noting that any concerns of a flood of similar withdrawals has yet to occur, but adds that the decision puts the African Court in good stead to consider similar applications, as long as the African Court adheres to a stricter timeline for the publication of such decisions.     TITRE ET RÉSUMÉ EN FRANCAIS: Evaluation du Rwexit: impact et conséquences du retrait par le Rwanda de sa déclaration de reconnaissance de la juridiction de la Cour africaine des droits de l’homme et des peuples faite aux termes de l’article 34(6)  RÉSUMÉ: Cet article examine le retrait de la déclaration du Rwanda autorisant les individus et les Organisations Non Gouvernementales à saisir directement la Cour africaine des droits de l'homme et des peuples, conformément à l'article 34(6) du Protocole à la Cour africaine. Ce retrait est une première dans la vie de la jeune juridiction et qui aurait pour but d’empêcher les personnes accusées de minimisation ou de négation du génocide d’avoir accès à la Cour africaine et apparait visiblement, par conséquent, comme une tentative de dénier à certains Rwandais une voie de recours pour faire valoir leurs droits. Cet article avance en outre que, confrontée au premier défi majeur à son autorité, la Cour africaine a rendu une décision bien motivée qui autorise le retrait, mais seulement après un délai de 12 mois, considéré comme un préavis. Ce qui est plus préoccupant est le retard de six mois mis pour rendre l’arrêt disponible au public, un fait regrettable eu égard particulièrement à l’option d’un retrait assorti d’un délai de préavis de 12 mois. L'article conclut en notant que la crainte d’une multiplication de retraits similaires ne s’est pas encore réalisée mais ajoute que la décision qu’elle a rendue met la Cour en état d’examiner des demandes similaires pour autant que de telles décisions soient publiées dans des délais plus strictes.
The effects of stochasticity at the single-cell level and cell size control on the population growth

Establishing a quantitative connection between the population growth rate and the generation times of single cells is a prerequisite for understanding evolutionary dynamics of microbes. However, existing theories fail to account for the experimentally observed correlations between mother-daughter generation times that are unavoidable when cell size is controlled for - which is essentially always the case. Here, we study population-level growth in the presence of cell size control and corroborate our theory using experimental measurements of single-cell growth rates. We derive a closed formula for the population growth rate and demonstrate that it only depends on the single-cell growth rate variability, not other sources of stochasticity. Our work provides an evolutionary rationale for the narrow growth rate distributions often observed in nature: when single-cell growth rates are less variable but have a fixed mean, the population will exhibit an enhanced population growth rate, as long as the correlations between the mother and daughter cells' growth rates are not too strong.
Citizen science as an instrument for women’s health research

Women’s health research is receiving increasing attention globally, but considerable knowledge gaps remain. Across many fields of research, active involvement of citizens in science has emerged as a promising strategy to help align scientific research with societal needs. Citizen science offers researchers the opportunity for large-scale sampling and data acquisition while engaging the public in a co-creative approach that solicits their input on study aims, research design, data gathering and analysis. Here, we argue that citizen science has the potential to generate new data and insights that advance women’s health. Based on our experience with the international Isala project, which used a citizen-science approach to study the female microbiome and its influence on health, we address key challenges and lessons for generating a holistic, community-centered approach to women’s health research. We advocate for interdisciplinary collaborations to fully leverage citizen science in women’s health toward a more inclusive research landscape that amplifies underrepresented voices, challenges taboos around intimate health topics and prioritizes women’s involvement in shaping health research agendas.
Dynamics and Thermodynamics of a model with long-range interactions

The dynamics and the thermodynamics of particles/spins interacting via long-range forces display several unusual features with respect to systems with short-range interactions. The Hamiltonian Mean Field (HMF) model, a Hamiltonian system of N classical inertial spins with infinite-range interactions represents a paradigmatic example of this class of systems. The equilibrium properties of the model can be derived analytically in the canonical ensemble: in particular the model shows a second order phase transition from a ferromagnetic to a paramagnetic phase. Strong anomalies are observed in the process of relaxation towards equilibrium for a particular class of out-of-equilibrium initial conditions. In fact the numerical simulations show the presence of quasi-stationary state (QSS), i.e. metastable states which become stable if the thermodynamic limit is taken before the infinite time limit. The QSS differ strongly from  Boltzmann-Gibbs equilibrium states: they exhibit negative specific heat, vanishing Lyapunov exponents and weak mixing, non-Gaussian velocity distributions and anomalous diffusion, slowly-decaying correlations and aging. Such a scenario provides strong hints for the possible application of Tsallis generalized thermostatistics. The QSS have been recently interpreted as a spin-glass phase of the model. This link indicates another promising line of research, which is not alternative to the previous one.
THERMODYNAMICS OF CHEMICAL ENGINES: A CHEMICAL REACTION NETWORK APPROACH

Chemical processes in closed systems inevitably relax to equilibrium. Energy can be employed to counteract such tendency and drive reactions against their spontaneous direction. This nonequilibrium driving is implemented in open systems, which living organisms provide the most spectacular examples of. In recent years, experiments in supramolecular chemistry, photochemistry and electrochemistry demonstrated that, by opening synthetic systems to matter and/or energy exchanges with the environment, artificial systems with life-like behaviours can be realized and used to convert energy inputs of different nature into work at both the nanoscopic and the macroscopic level. However, one tool that is still lacking is a firm grasp of the thermodynamics of these chemical engines. In this thesis, we provide it by leveraging the most recent developments of the thermodynamic description of deterministic chemical reaction networks. As main theoretical results, we extend the current theory to encompass nonideal and light-driven systems, thus providing the fundamental tools to treat electrochemical and photochemical systems in addition to the chemically driven ones. We also expand the scope of information thermodynamics to bipartite chemical reaction networks characterized by macroscopic non-normalized concentration distributions evolving in time with nonlinear dynamics. This framework potentially applies to almost every synthetic chemical engine realized until now, and to many models of biological systems too. Here, we undertake the thermodynamic analysis of some of the epitomes in the field of artificial chemical engines: a model of chemically driven self-assembly, an experimental chemically driven molecular motor, and an experimental photochemical bimolecular pump. The thesis provides a thermodynamic level of understanding of chemical engines that is general, complements previous analyses based on kinetics and stochastic thermodynamics, and has practical implications for designing and improving synthetic systems, regardless of the particular type of powering or chemical structure.
Predicting drug-drug interactions with physiologically based pharmacokinetic/pharmacodynamic modelling and optimal dosing of apixaban and rivaroxaban with dronedarone co-administration

The concurrent administration of dronedarone and oral anti-coagulants is common because both are used in managing atrial fibrillation (AF). Dronedarone is a moderate inhibitor of the cytochrome P450 3A4 (CYP3A4) enzyme and P-glycoprotein (P-gp). Apixaban and rivaroxaban are P-gp and CYP3A4 substrates. This study aims to investigate the impact of exposure and bleeding risk of apixaban or rivaroxaban when co-administered with dronedarone using physiologically based pharmacokinetic/pharmacodynamic analysis.Modeling and simulation were conducted using Simcyp® Simulator. The parameters required for dronedarone modeling were collected from the literature. The developed dronedarone physiologically based pharmacokinetic (PBPK) model was verified using reported drug-drug interactions (DDIs) between dronedarone and CYP3A4 and P-gp substrates. The model was applied to evaluate the DDI potential of dronedarone on the exposure of apixaban 5 mg every 12 h or rivaroxaban 20 mg every 24 h in geriatric and renally impaired populations. DDIs precipitating major bleeding risks were assessed using exposure-response analyses derived from literature.The model accurately described the pharmacokinetics of orally administered dronedarone in healthy subjects and accurately predicted DDIs between dronedarone and four CYP3A4 and P-gp substrates with fold errors &lt;1.5. Dronedarone co-administration led to a 1.29 (90 % confidence interval (CI): 1.14-1.50) to 1.31 (90 % CI: 1.12-1.46)-fold increase in the area under concentration-time curve for rivaroxaban and 1.33 (90 % CI: 1.15-1.68) to 1.46 (90 % CI: 1.24-1.92)-fold increase for apixaban. The PD model indicated that dronedarone co-administration might potentiate the mean major bleeding risk of apixaban with a 1.45 to 1.95-fold increase. However, the mean major bleeding risk of rivaroxaban was increased by &lt;1.5-fold in patients with normal or impaired renal function.Dronedarone co-administration increased the exposure of rivaroxaban and apixaban and might potentiate major bleeding risks. Reduced apixaban and rivaroxaban dosing regimens are recommended when dronedarone is co-administered to patients with AF.