ethicalabs/Research-Intent-Collab huggingface dataset:
Forest Land Tenure Rights on Indigenous Peoples in Honitetu Village West Seram District, Maluku

Forest land tenure systems for indigenous peoples are always debated by various parties regarding the overlapping interests and rights of forest land. Objective of this study is to analyze the types of indigenous peoples' rights to strengthen forest land tenure systems in Honitetu Village, West Seram Regency. The research approach used is Participatory Action Research by building constructs of meaning between researchers and society repeatedly to obtain an understanding of the information discussed. Data were obtained through key informant interviews and focus group discussions conducted repeatedly. The analysis was carried out at each stage of the interview and discussion by making categorization of data to get an understanding of each data obtained. The results of study show that the system of forest land tenure in indigenous communities in Honite village includes control by the whole community (petuanan), control by clan groups (soa) and control by individuals (families). In these three systems, various types of rights are attached to managing and utilizing forest resources. The set of rights contained in indigenous peoples will be even stronger if it includes the linkage of longtime dimensions, the dimensions of space for the use of vertical or horizontal space, the dimensions of the subject with fixed ownership and the dimensions of the object include the results of forest land that provides full benefits. Key words: forest land tenure rights, indigenous people, forest management
The precautionary principle in times of intermingled uncertainty and risk: some regulatory complexities

This article explores the use of the precautionary principle in situations of intermingled uncertainty and risk. It analyses how the so-called uncertainty paradox works out by examining the Pfizer case. It reveals regulatory complexities that result from contradictions in precautionary thinking. In conclusion, a plea is made for embedment of uncertainty information, while stressing the need to rethink regulatory reform in the broader sense.
A review on applied Natural Language Processing to Electronic Health Records

Over the last decades, the healthcare sector has witnessed massive growth in the use of various information technologies such as Electronic Health Records (EHRs), a digital version of a patient's paper chart that electronically stores all information related to patient care. After the emergence of the EHRs, a large amount of language data is being produced. This data is a collection of documents or text files that include essential information, but most of them are unstructured to be properly analyzed by computers. To handle the human language complexity and make this data more machine-analyzable, researchers often rely on using Natural Language Processing (NLP) techniques. This paper presents a review that features the application of NLP and machine learning to EHRs and present associated challenges. Besides, we outline various applications and initiatives in the healthcare sector. Finally, we provide promising directions for future research.
Relating Structure to Electrochemistry: I                n-Situ Studies of Fe[Fe(CN)<sub>6</sub>] As Cathode Materials for Rechargeable Li- and Na-Ion Batteries

The Prussian blue type compound Fe[Fe(CN)6] is investigated as a cathode material for use in rechargeable Li- and Na-ion batteries. The structural changes following electrochemical Li+ and Na+ ion insertion during charge-discharge cycles were followed using in-situ X-ray and neutron powder diffraction techniques.1-3                                The electrochemical performance of Fe[Fe(CN)6] has been investigated for both Li+ and Na+ ions with capacities of 100 and 115 mA h g-1 respectively. Further investigations of the Na-ion cells for Fe[Fe(CN)6] show the capacity to depend on the heating temperature used in preparing the cathode material. Fe[Fe(CN)6] heated at 110 °C shows the highest capacity of 115 mA h g-1, with capacity fading to 75 mA h g-1 when the framework is heated at 150 °C. Cells containing samples of Fe[Fe(CN)6] heated at 110 °C show excellent capacity retention of more than 99% after 50 cycles.                                   In-situ synchrotron X-ray diffraction has been performed for the Na-ion cells, while in-situneutron diffraction studies were carried out on Li-ion cells. In both cases, these allow for the direct correlation of structural changes to the cathode material and the observed electrochemical properties, as both are collected simultaneously.                (1)        Roberts, M.; Biendicho, J. J.; Hull, S.; Beran, P.; Gustafsson, T.; Svensson, G.; Edström, K. Journal of Power Sources                    2013, 226, 249.                (2)        Sharma, N.; Peterson, V. J. Solid State Electrochem.                    2012, 16, 1849.                (3)        Bergstöm, Ö.; Andersson, A. M.; Edström, K.; Gustafsson, T. J. Appl. Crystallogr.                    1998, 31, 823.
Constrained Cosmological Simulations of Dark Matter Halos

5 pages, 2 postscript figures, ApJ emulator, submitted to ApJ Letters
Predicting Survival within the Lung Cancer Histopathological Hierarchy Using a Multi-Scale Genomic Model of Development

The histopathologic heterogeneity of lung cancer remains a significant confounding factor in its diagnosis and prognosis-spurring numerous recent efforts to find a molecular classification of the disease that has clinical relevance.Molecular profiles of tumors from 186 patients representing four different lung cancer subtypes (and 17 normal lung tissue samples) were compared with a mouse lung development model using principal component analysis in both temporal and genomic domains. An algorithm for the classification of lung cancers using a multi-scale developmental framework was developed. Kaplan-Meier survival analysis was conducted for lung adenocarcinoma patient subgroups identified via their developmental association. We found multi-scale genomic similarities between four human lung cancer subtypes and the developing mouse lung that are prognostically meaningful. Significant association was observed between the localization of human lung cancer cases along the principal mouse lung development trajectory and the corresponding patient survival rate at three distinct levels of classical histopathologic resolution: among different lung cancer subtypes, among patients within the adenocarcinoma subtype, and within the stage I adenocarcinoma subclass. The earlier the genomic association between a human tumor profile and the mouse lung development sequence, the poorer the patient's prognosis. Furthermore, decomposing this principal lung development trajectory identified a gene set that was significantly enriched for pyrimidine metabolism and cell-adhesion functions specific to lung development and oncogenesis.From a multi-scale disease modeling perspective, the molecular dynamics of murine lung development provide an effective framework that is not only data driven but also informed by the biology of development for elucidating the mechanisms of human lung cancer biology and its clinical outcome.
Educating students about sex is like giving them a gift, without being allowed to open it. - A study about students’ attitudes towards Sexual and reproductive health and rights education in Moshi, Tanzania

The study was conducted in Moshi, the regional Capital of Kilimanjaro region, Tanzania. It was financed by Sida’s Minor Field Study scholarship in March and April 2019. This study was carried out at a Secondary school and focuses on students’ attitudes and knowledge about sexual and reproductive health and rights, SRHR, as well as examine how different actors influence the students’ decision-making and attitudes in Form 4. Qualitative semi-structured interviews are conducted, combined with the use of flashcards, as a method. Each flashcard contains topics within the concept of SRHR and was based on previous research and definitions. The use of flashcards was conducted in two steps. Firstly, the students’ categorized SRHR-topics in five different categories. Secondly, the students’ ranked ten actors in which affect them the most to least. Most of the students believe that most of the topics are important to learn about but in a future context. They also believe that education in some topics will result in increased sexual behavior. The students identify that authorities, such as parents and school, affect them the most in their decision-making and attitudes. To conclude, the students were found to have limited education focusing on attitudes as well as access to evidence-based education.
Using Coupling Methods to Estimate Sample Quality of Stochastic Differential Equations

A probabilistic approach for estimating sample qualities for stochastic differential equations is introduced in this paper. The aim is to provide a quantitative upper bound of the distance between the invariant probability measure of a stochastic differential equation and that of its numerical approximation. In order to extend estimates of finite time truncation error to infinite time, it is crucial to know the rate of contraction of the transition kernel of the SDE. We find that suitable numerical coupling methods can effectively estimate such rate of contraction, which gives the distance between two invariant probability measures. Our algorithms are tested with several low and high dimensional numerical examples.
An Overview on the Probabilistic Safety Assessment (PSA), the Loss of External Power Source Connected to the Nuclear Power Plant

Loss of Offsite Power source connected to the nuclear power plant (LOOP) as the starter event and consequently the probability Station Blackout (SBO) are among accidents that are considered in the Probabilistic Safety Assessment (PSA) and have a significant impact on the melting frequency of the reactor core. Thus, in this paper, the Probabilistic Safety Assessment (PSA), the loss of the external power source in the nuclear power plant is investigated.
Designing for Engagement: How Self-Determination Theory Can Guide Digital Health Design for User Motivation

User engagement is crucial for the efficacy of digital health and mental health interventions, yet existing design strategies for improving engagement remain heterogeneous, context-specific, and insufficiently grounded in motivational theory. In this paper, we propose a preliminary, theory-grounded design framework that draws on Self-Determination Theory (SDT) and its sub-theory, Organismic Integration Theory (OIT), to guide the design of digital health interventions for sustained user engagement. Informed by existing literature and our own empirical data from surveys (N = 438), interviews (N = 31), and co-design workshops (N = 59) with end users, the framework categorises design strategies across the adoption, interface, and task spheres of the user experience, distinguishing between those that primarily support intrinsic motivation and those that foster autonomous forms of extrinsic motivation. We argue that this distinction is critical: strategies commonly grouped under umbrella terms such as gamification in fact operate through different motivational channels and should be designed and evaluated accordingly. By clarifying these motivational pathways, our framework aims to support researchers and practitioners in designing digital health interventions that not only facilitate initial uptake but also enhance the internalisation of health behaviours for long-term, sustained engagement. We present this framework as a basis for discussion at this workshop, inviting expert feedback and critique to refine it as a contribution to the field.
QMM‐Enhanced Error Correction: Demonstrating Reversible Imprinting and Retrieval for Robust Quantum Computation

Abstract                   The first hardware evidence is reported that a Quantum Memory Matrix (QMM) ‐ conceived as a Planck‐scale lattice of finite‐dimensional memory cells ‐ functions as an ultra‐shallow, measurement‐free error‐suppression layer for noisy intermediate‐scale quantum processors. On a seven‐qubit IBM transmon device, quantum states are imprint onto local cells with single‐qubit  and nearest‐neighbor  gates and later retrieve them through a controlled‐SWAP, guaranteeing unitary reversibility. A single imprint–retrieval cycle attains a hardware fidelity of ; prepending the same layer to a conventional  repetition code boosts the logical fidelity to  ‐ a 32 % improvement obtained without additional CX gates. Incorporating the layer into a variational quantum classifier lowers the final training loss by 35 % and halves run‐to‐run variance, evidencing its value for hybrid quantum‐classical workloads. Noise‐calibrated simulations further show that stacking three QMM layers brings the logical error rate to within 20 % of a distance‐three surface code while using an order of magnitude fewer qubits. Because the QMM booster is fully unitary and eschews mid‐circuit measurement, it is directly compatible with platforms where rapid stabilizer read‐out is impractical and provides empirical support for the broader notion that space‐time itself may behave as a distributed quantum memory.
The Impact of Social Media on Adolescent Mental Health: A Meta-Analysis

Introduction: The proliferation of social media has raised significant concerns about its potential effects on the mental health of adolescents. This meta-analysis aims to provide a comprehensive assessment of the existing research on the relationship between social media use and various mental health outcomes in adolescents.  Methods: A systematic search of electronic databases (PubMed, PsycINFO, Scopus, Web of Science) from January 2018 to June 2024 was conducted to identify relevant studies. Studies were included if they examined the association between social media use and mental health outcomes in adolescents (aged 10-19) and reported quantitative data. Effect sizes were calculated and pooled using random-effects models.  Results: A total of 45 studies (N = 153,285 adolescents) met the inclusion criteria. The meta-analysis revealed small but significant associations between increased social media use and increased depressive symptoms (r = 0.12), anxiety (r = 0.10), and loneliness (r = 0.15). Furthermore, a significant negative association was found between social media use and self-esteem (r = -0.08). The analysis also identified several moderators of these effects, including gender, age, and type of social media platform.  Conclusion: The findings of this meta-analysis suggest that increased social media use is associated with a range of negative mental health outcomes in adolescents. However, the effects are small, and the relationship is complex, with several moderating factors. Further research is needed to understand the mechanisms underlying these associations and to develop effective interventions to mitigate the potential negative effects of social media on adolescent mental health.
Projections of future changes in solar radiation in China based on CMIP5 climate models

Surface solar radiation research is important for understanding future climate change and the application of large-scale photovoltaic systems. We used the coupled model intercomparison project phase 5 (CMIP5) under the RCP8.5 scenario to project potential changes in surface solar radiation, surface temperatures, and cloud fractions between 2006 and 2049 in China, as well as how these changes may affect photovoltaic power generation. The results show that the following. (1) For surface temperatures, the median trends of all considered models show warming in China of 0.05 K/year. The maximum positive trends for all-sky radiation appear in the southeast of China, reaching 0.4 W/m2/year. Cloud cover exhibits a mainly decreasing trend in the overall region of China. (2) The all-sky radiation of most selected regions shows a decreasing trend. The maximum negative value (−0.08 W/m2/year) appears in Qinghai. (3) Compared with the average photovoltaic power output from 2006 to 2015, the photovoltaic power output in western China will decrease by −0.04 %/ year, while photovoltaic power output in southeastern China will increase by 0.06–0.1%/year. Keywords: Solar radiation changes, CMIP5 models, Climate change, PV output, Projections
Are decisions well supported for the energy transition? A review on modeling approaches for renewable energy policy evaluation

This study reviews energy policy evaluation approaches on their capability to estimate a successful implementation of renewable energy policies. This is predominantly done via energy system modeling and analysis. Although modeling the possible success and effects is not a precondition for policy making, it is a powerful tool to support decision makers in policy making. This awareness has led to the development of numerous modeling approaches with many case studies. Therefore, effort has to be made to evaluate recent modeling approaches that could be suitable for renewable energy policy evaluation. It is the aim of this paper to provide an overview on recent renewable energy policy modeling approaches that are capable in evaluating the success and side effects to other sectors of renewable energy policies. We will highlight advantages and drawbacks of these approaches and provide a framework assessing the suitability of the presented methodologies for the evaluation of renewable energy policies. We provide a tabular overview that enables the reader to quickly derive information on the suitability of the several modeling approaches to evaluate renewable energy policies.
Application scenario-oriented molecule generation platform developed for drug discovery

Design of molecules for candidate compound selection is one of the central challenges in drug discovery due to the complexity of chemical space and requirement of multi-parameter optimization. Here we present an application scenario-oriented platform (ID4Idea) for molecule generation in different scenarios of drug discovery. This platform utilizes both library or rule based and generative based algorithms (VAE, RNN, GAN, etc.), in combination with various AI learning types (pre-training, transfer learning, reinforcement learning, active learning, etc.) and input representations (1D SMILES, 2D graph, 3D shape, binding site, pharmacophore, etc.), to enable customized solutions for a given molecular design scenario. Besides the usual generation followed screening protocol, goal-directed molecule generation can also be conducted towards predefined goals, enhancing the efficiency of hit identification, lead finding, and lead optimization. We demonstrate the effectiveness of ID4Idea platform through case studies, showcasing customized solutions for different design tasks using various input information, such as binding pockets, pharmacophores, and compound representations. In addition, remaining challenges are discussed to unlock the full potential of AI models in drug discovery and pave the way for the development of novel therapeutics.
Lost in translation: key lessons from conducting dissemination and implementation science in Zambia

As the field of implementation science continues to grow, its key concepts are being transferred into new contexts globally, such as Low and Middle Income Countries (LMICs), and its use is constantly being reexamined and expanded. Theoretical and methodological positions commonly used in implementation research and practice have great utility in our work but in many cases are at odds with LMIC contexts. As a team of implementation scientists based in Zambia, we offer this commentary as a critical self-reflection on what has worked and what could limit us from fully utilizing the field's promise for addressing health problems with contextual understanding.We used a 'premortem,' an approach used to generate potential alternatives from failed assumptions about a particular phenomenon, as a way to reflect on our experiences conducting implementation research and practice. By utilizing prospectively imagined hindsights, we were able to reflect on the past, present and possible future of the field in Zambia. Six key challenges identified were: (i) epistemic injustices; (ii) simplified conceptualizations of evidence-informed interventions; (iii) limited theorization of the complexity of low-resource contexts and it impacts on implementation; (iv) persistent lags in transforming research into practice; (v) limited focus on strategic dissemination of implementation science knowledge and (vi) existing training and capacity building initiatives' failure to engage a broad range of actors including practitioners through diverse learning models.Implementation science offers great promise in addressing many health problems in Zambia. Through this commentary, we hope to spur discussions on how implementation scientists can reimagine the future of the field by contemplating on lessons from our experiences in LMIC settings.
Rule of law and judicial independence

The rule of law and judicial independence are a project yet to be achieved in Mozambique. The different attempts made so far to reform the legal system, mainly after the change in political and strategic direction brought about by the Constitution of 1990, were always short-sighted and conjunctural in nature, under domestic and foreign pressure that was not always clear or well-intentioned. Real structural reforms need to be made for the judiciary to be able to affirm itself as a real power and, in this way, favour balanced growth of companies, increased productivity, investment and jobs and, at the same time, the defence of the rights and legitimate interests of individuals and groups with fewer economic resources.
Deliberative Technology for Alignment

For humanity to maintain and expand its agency into the future, the most powerful systems we create must be those which act to align the future with the will of humanity. The most powerful systems today are massive institutions like governments, firms, and NGOs. Deliberative technology is already being used across these institutions to help align governance and diplomacy with human will, and modern AI is poised to make this technology significantly better. At the same time, the race to superhuman AGI is already underway, and the AI systems it gives rise to may become the most powerful systems of the future. Failure to align the impact of such powerful AI with the will of humanity may lead to catastrophic consequences, while success may unleash abundance. Right now, there is a window of opportunity to use deliberative technology to align the impact of powerful AI with the will of humanity. Moreover, it may be possible to engineer a symbiotic coupling between powerful AI and deliberative alignment systems such that the quality of alignment improves as AI capabilities increase.
Historical Perspectives in Ecology and Evolutionary Biology: The Use of Phylogenetic Comparative Analyses

Hypotheses about the adaptive significance of a trait have long been tested by making comparisons among species. Many recent studies emphasized that conclusions about the origin and maintenance of adaptations as well as the underlying selective processes derived from comparative tests may be strengthened with the inclusion of a phylogenetic hypothesis. Major advances in the comparative approach have therefore occurred with the coincident developments in numerical methods available for phylogenetic inference. In this review, we outline the advantages and possible disadvantages of adopting an historical approach in ecological and evolutionary studies. We begin by discussing the need for including informatipn on the phyletic relationships among taxa in ecological and evolutionary analyses. Next we describe how an historical approach not only refines the definition and recognition of adaptations, but also provides an objective definition of "phylogenetic constraints." Because conceptual and analytical advances in comparative methods are occurring quite rapidly, we provide a brief summary of the goals,