ethicalabs/Research-Intent-Collab huggingface dataset:
Phylo-evo-devo: combining phylogenetics with evolutionary developmental biology

As a result of the integration of molecular and morphological approaches for the reconstruction of phylogenies, and of the intertwining of developmental and evolutionary biology, further prospects are open for a fruitful interaction between these two fields in what we may call a phylo-evo-devo approach.Wiegmann et al.'s molecular phylogeny of the holometabolous insect orders, recently published in BMC Biology, offers a good opportunity to revisit the inverted positions of wings and halteres in the Diptera and the Strepsiptera in terms of a putative homeotic mutation in the Hox gene Ultrabithorax. The main finding of this paper is that Strepsiptera are closely related to the Coleoptera rather than Diptera, as recently claimed. Through this exemplary case, the paper demonstrates the value of the reciprocal illumination we can expect from the integration of a good phylogeny and a sound knowledge of the evolvability of developmental mechanisms.
The effects of personal information on competition: Consumer privacy and partial price discrimination

This article studies the effects of consumer information on the intensity of competition. In a two dimensional duopoly model of horizontal product differentiation, firms use consumer information to price discriminate. I contrast a full privacy and a no privacy benchmark with intermediate regimes in which the firms target consumers only partially. No privacy is traditionally detrimental to industry profits. Instead, I show that with partial privacy firms are always better-off with price discrimination: the relationship between information and profits is hump-shaped. Consumers prefer either no or full privacy in aggregate. However, even though this implies that privacy protection in digital markets should be either very hard or very easy, the effects of information on individual surplus are ambiguous: there are always winners and losers. When an upstream data seller holds partially informative data, an exclusive allocation arises. Instead, when data is fully informative, each competitor acquires consumer data but on a different dimension.
RULE OF LAW IN THE SOUTHERN MEDITERRANEAN. FROM JUDICIAL INDEPENDENCE TO EFFICIENCY: AN INTERNAL-EXTERNAL EXPLANATORY APPROACH OF EU JUDICIAL SUPPORT IN MOROCCO AND JORDAN.

As the crisis of 2011, known as the Arab Spring, broke out, two monarchies in the region, Morocco and Jordan, faced the need to reform their judicial systems in order to preserve stability by means of constitutional reforms that would deliver both countries from poor guarantees of judicial independence and lack of transparency or efficiency. This research thesis will analyse the external and internal dynamics of judicial reforms adopted in Morocco and Jordan since 2011. In particular, we have chosen an important empirical field where the two most similar countries receiving external support to judicial reforms show a variation on the judicial systemic level. This variation is still unexplored and our knowledge of the dynamics of domestic veto players and external support to the judiciary could be further enhanced through comparative analysis of two most similar cases using a Most Similar Systems Design (Mill 1882).
Editorial: Improving the clinical value of digital phenotyping in mental health

مقالة افتتاحية الجبهة. الطب النفسي، 18 يوليو 2023Sec. مجلد الصحة العقلية الرقمية 14 - 2023 | https://doi.org/10.3389/fpsyt.2023.1251930
On Lands and Dispossession. The Relevance and Potential of Property Law for the Constitutional Recognition of the Rights of Indigenous Peoples

This paper intends to consider whether and how minorities, especially Indigenous groups, can and should be protected in Constitutions through property law rules, and it investigates the role that constitutional formants can play in the recognition of multiculturalism and pluralism, dealing with the Brazilian legal system as a case study. To do so, this article seeks to establish whether the constitutional acknowledgment of ancestral land ownership of Indigenous communities can be a way to safeguard both their rights and, more broadly, other collective interests of society, such as multiculturalism and environmental protection. This essay adopts an interdisciplinary methodology, combining comparative private and constitutional law with an historical perspective. The aim is to valorize the right to property as a vehicle to promote the rights of Indigenous groups, and ensure social justice, taking into account the peculiarities of Latin American legal systems.
Diverse correlation structures in gene expression data and their utility in improving statistical inference

It is well known that correlations in microarray data represent a serious nuisance deteriorating the performance of gene selection procedures. This paper is intended to demonstrate that the correlation structure of microarray data provides a rich source of useful information. We discuss distinct correlation substructures revealed in microarray gene expression data by an appropriate ordering of genes. These substructures include stochastic proportionality of expression signals in a large percentage of all gene pairs, negative correlations hidden in ordered gene triples, and a long sequence of weakly dependent random variables associated with ordered pairs of genes. The reported striking regularities are of general biological interest and they also have far-reaching implications for theory and practice of statistical methods of microarray data analysis. We illustrate the latter point with a method for testing differential expression of nonoverlapping gene pairs. While designed for testing a different null hypothesis, this method provides an order of magnitude more accurate control of type 1 error rate compared to conventional methods of individual gene expression profiling. In addition, this method is robust to the technical noise. Quantitative inference of the correlation structure has the potential to extend the analysis of microarray data far beyond currently practiced methods.
INTERNATIONAL HUMANITARIAN LAW IN INTERNAL ARMED CONFLICT: IMPLEMENTING COMMON ARTICLE 3 AND ADDITIONAL PROTOCOL II TO THE GENEVA CONVENTIONS TO INTERNAL AND HORIZONTAL CONFLICTS IN INDONESIA

This research explores the applicability of Article 3 of the Geneva Conventions of 1949 and Additional Protocol II 1977 of the Geneva Conventions of 1949 through internal and horizontal conflicts, and the minimum threshold of'internal armed conflict and internal civil disturbances' in Indonesia, such as in Kalimantan, Paso and Maluku
Biodiversity and Conservation Ecology of the Hyrcanian Forests, Northern Iran: Patterns, Threats, and Management Perspectives

The Hyrcanian forests, extending along the southern coast of the Caspian Sea, represent one of the world’s most ancient temperate broadleaf forest ecosystems and were inscribed as a UNESCO World Heritage Site in 2019. Encompassing over 1.9 million hectares across the northern slopes of the Alborz Mountains, these forests harbor exceptional levels of biodiversity, endemism, and ecological complexity. However, anthropogenic pressures—including deforestation, agricultural encroachment, and climate-induced shifts—have significantly altered their composition and functioning. This study synthesizes the ecological patterns, biodiversity gradients, and conservation challenges of the Hyrcanian forests using an integrative framework that combines species distribution data, ecological trait analysis, and landscape-scale conservation approaches. Data were gathered from 40 peer-reviewed studies (2000–2024) and international databases (GBIF, FAO, UNEP-WCMC). The results reveal high spatial heterogeneity driven by topographic gradients and climatic variability, with Fagus orientalis–dominated forests occupying mid- to high-elevation zones and mixed Quercus–Carpinus communities dominating lower elevations. Threat assessments show that more than 40% of the Hyrcanian area has been degraded, with the most significant pressures arising from illegal logging, infrastructure expansion, and overgrazing. Conservation recommendations include expansion of protected areas, ecosystembased management, and the adoption of community-based conservation models. The study concludes that preserving the Hyrcanian biodiversity hotspot requires integrated policy frameworks, trait-based restoration planning, and climate-resilient management strategies.  Keywords: Hyrcanian forests, biodiversity, conservation ecology, ecosystem management, Iran, restoration, endemism
Effects of the position of the solar wind termination shock and the heliopause on the heliospheric modulation of cosmic rays

Abstract   The effects of changing the position of the solar wind termination shock and the position of the heliopause, and therefore the extent of the heliosheath, on the modulation of cosmic ray protons are illustrated. An improved numerical model with diffusive termination shock acceleration, a heliosheath and drifts is used. The modulation is computed in the equatorial plane and at 35 heliolatitude using recently derived diffusion coefficients applicable to a number of cosmic ray species during both magnetic polarity cycles of the Sun. It was found that qualitatively the modulation results for the different heliopause positions are similar although they differ quantitatively, e.g., clearly different radial gradients are predicted for the regions beyond the termination shock compared to inside the shock. The difference between the modulation for the two solar polarity cycles are less significant at a heliolatitude of 35° than in the equatorial plane. We found that moving the termination shock from 90 to 100 AU, with the heliopause fixed at 120 AU, caused only quantitative differences so that the exact position of the TS in the outer heliosphere seems not crucially important to global modulation. Moving the heliopause outwards, to represent the modulation in the tail region of the heliosphere, causes overall decreases in the cosmic ray intensities but not linearly as a function of energy, e.g., at 1 GeV the effect is insignificant. We conclude from this modelling that the modulation of protons in the heliospheric nose and tail regions are qualitatively similar although, clear quantitative and interesting differences occur.
Limited Support for Trunk and Hip Deficits as Risk Factors for Athletic Knee Injuries: A Systematic Review With Meta-analysis and Best-Evidence Synthesis

Objective To determine whether neuromuscular deficits in trunk and hip-related function are risk factors for athletic knee injuries. Design Etiology systematic review with meta-analysis. Literature Search Six online databases (MEDLINE, Web of Science, Embase, CINAHL, Scopus, and SPORTDiscus) were searched up to April 2019. Study Selection Criteria Studies assessing trunk and hip neuromuscular function as risk factors for knee injuries in healthy athletic populations were included. Data Synthesis Outcomes were synthesized quantitatively using meta-analysis of odds ratios, and qualitatively using best-evidence synthesis. Results Twenty-one studies met the inclusion criteria. There was very low–certainty evidence that greater hip external rotation strength protected against knee injuries (odds ratio = 0.78; 95% confidence interval: 0.70, 0.87; P&lt;.05). There was limited evidence that deficits in trunk proprioception and neuromuscular control, and the combination of excessive knee valgus and ipsilateral trunk angle when landing unilaterally from a jump, may be risk factors for knee injuries. Conclusion Most variables of trunk and hip function were not risk factors for injuries. Further research is required to confirm whether hip external rotation strength, trunk proprioception and neuromuscular control, and the combination of knee valgus angle and ipsilateral trunk control are risk factors for future knee injuries. J Orthop Sports Phys Ther 2020;50(9):476–489. Epub 1 Aug 2020. doi:10.2519/jospt.2020.9705
Marketing Experimental Stem Cell Therapies in the UK: Biomedical Lifestyle Products and the Promise of Regenerative Medicine in the Digital Era

Stem cell research has attracted much public and biomedical anticipation centred on the possibility of using stem cells to treat various diseases and conditions, but the number of evidence-based therapies is currently limited. Numerous commercial direct-to-consumer (DTC) businesses are nonetheless marketing experimental stem cell therapies online for myriad medical conditions and aesthetic ailments, which has attracted critique due to safety and efficacy concerns. Existing research has largely focused on the problem of unproven therapies and regulatory pathways for addressing it. The proliferation of these experimental products must also be examined, however, in the broader socio-technological context of consumer culture and changing practices of knowledge-making in the digital era. DTC stem cell therapies have emerged as a new biomedical 'lifestyle' product that blurs the boundaries between 'science,' 'medicine,' and 'consumer culture.' In using, conceptualising and marketing stem cells, commercial businesses build on and commercially co-opt alternative epistemic and ontological frames that challenge scientific medicine. They advance promissory narratives about their potential that tap on cultural aspirations around the future of medicine and health. This is key, not only for understanding how and why these therapies have proliferated but also in conceptualising what the 'problem' around them actually is.
Predicting drug response of tumors from integrated genomic profiles by deep neural networks

The study of high-throughput genomic profiles from a pharmacogenomics viewpoint has provided unprecedented insights into the oncogenic features modulating drug response. A recent screening of ~1,000 cancer cell lines to a collection of anti-cancer drugs illuminated the link between genotypes and vulnerability. However, due to essential differences between cell lines and tumors, the translation into predicting drug response in tumors remains challenging. Here we proposed a DNN model to predict drug response based on mutation and expression profiles of a cancer cell or a tumor. The model contains a mutation and an expression encoders pre-trained using a large pan-cancer dataset to abstract core representations of high-dimension data, followed by a drug response predictor network. Given a pair of mutation and expression profiles, the model predicts IC50 values of 265 drugs. We trained and tested the model on a dataset of 622 cancer cell lines and achieved an overall prediction performance of mean squared error at 1.96 (log-scale IC50 values). The performance was superior in prediction error or stability than two classical methods and four analog DNNs of our model. We then applied the model to predict drug response of 9,059 tumors of 33 cancer types. The model predicted both known, including EGFR inhibitors in non-small cell lung cancer and tamoxifen in ER+ breast cancer, and novel drug targets. The comprehensive analysis further revealed the molecular mechanisms underlying the resistance to a chemotherapeutic drug docetaxel in a pan-cancer setting and the anti-cancer potential of a novel agent, CX-5461, in treating gliomas and hematopoietic malignancies. Overall, our model and findings improve the prediction of drug response and the identification of novel therapeutic options.
Neural Architecture Search via Differentiable Proxies in AUTOML

Neural Architecture Search (NAS) automates the design of deep neural network architectures, potentially surpassing human-crafted designs across diverse tasks. However, the computational cost of evaluating candidate architectures has historically limited NAS scalability, with early methods requiring thousands of GPU-hours per search. Differentiable NAS methods address this by relaxing the discrete architecture selection into a continuous optimization problem amenable to gradient-based optimization. This paper provides a comprehensive survey of differentiable NAS approaches, with particular emphasis on proxy-based methods that further reduce computational overhead. We trace the evolution from DARTS through its failure modes and subsequent corrections, examine zero-cost proxies that estimate architecture quality without training, analyze one-shot and supernet-based approaches, and discuss training-free NAS methods grounded in neural tangent kernel theory. We present extensive empirical comparisons across standard NAS benchmarks (NAS-Bench-101, NAS-Bench-201, DARTS search space) and discuss the proxy gap between search and evaluation performance. Our analysis reveals that the field has progressed from methods requiring thousands of GPU-hours to approaches achieving competitive results in seconds, fundamentally transforming the accessibility of automated architecture design.
FROM INNOVATION TO REGULATION: ETHICAL GOVERNANCE OF AI IN TEACHING AND LEARNING

This study examines the policy and ethical issues surrounding the implementation of Artificial Intelligence (AI) in higher education teaching and learning. With AI tools quickly finding their way into the classroom, which has been facilitated by AI in examining assessment, tutoring, feedback, and instructional design, they have also brought about the privacy, bias, transparency, academic integrity, and the changing role of educators. The aim of the study is to chart these ethical emerging issues and determine the strengths and weaknesses in the existing institutional and international policies regulating the utilization of AI in teaching. Peer-reviewed articles, institutional guidelines, and global policy documents published since 2020 to 2025 were used to carry out a qualitative scoping review. The PRISMA criteria were used to filter sources. Trends were classified by thematic analysis to categorize them into five areas, data governance, fairness and bias, pedagogical autonomy, student well-being, and accountability in AI-assisted decision-making. University and accreditation policy documents, as well as policy documents of various organizations like UNESCO, OECD, and EDUCAUSE, were compared in order to evaluate their coherence and readiness to implement. The findings suggest that although educational institutions of higher learning are becoming more responsive to the risks of ethical issues, policies are usually general, inconsistent, and responsive. The transparency of algorithms and their responsible use in grading and assessment is not well-advised, and there are no systems that can be used to track the long-term educational effect of AI. The faculty and students are not always clear on what they can do with the use, and this has resulted in uneven adoption. Better systems are required to provide responsible uses of AI that safeguard academic values and encourage equity and meaningful human supervision. The research identifies the necessity of standardized rules, policy creation, and constant training of teachers to make recommendation of ethical and sustainable integration of AI.
Regulation of epigenetic state by non-histone chromatin proteins and transcription factors: Implications in disease

Besides the fundamental components of the chromatin, DNA and octameric histone, the non-histone chromatin proteins and non-coding RNA play a critical role in the organization of functional chromatin domains. The non-histone chromatin proteins therefore regulate the transcriptional outcome in both physiological and pathophysiological state as well. They also help to maintain the epigenetic state of the genome indirectly. Several transcription factors and histone interacting factors also contribute in the maintenance of the epigenetic states, especially acetylation by the induction of autoacetylation ability of p300/CBP. Alterations of KAT activity have been found to be causally related to disease manifestation, and thus could be potential therapeutic target.
Pathology-and-genomics Multimodal Transformer for Survival Outcome Prediction

Survival outcome assessment is challenging and inherently associated with multiple clinical factors (e.g., imaging and genomics biomarkers) in cancer. Enabling multimodal analytics promises to reveal novel predictive patterns of patient outcomes. In this study, we propose a multimodal transformer (PathOmics) integrating pathology and genomics insights into colon-related cancer survival prediction. We emphasize the unsupervised pretraining to capture the intrinsic interaction between tissue microenvironments in gigapixel whole slide images (WSIs) and a wide range of genomics data (e.g., mRNA-sequence, copy number variant, and methylation). After the multimodal knowledge aggregation in pretraining, our task-specific model finetuning could expand the scope of data utility applicable to both multi- and single-modal data (e.g., image- or genomics-only). We evaluate our approach on both TCGA colon and rectum cancer cohorts, showing that the proposed approach is competitive and outperforms state-of-the-art studies. Finally, our approach is desirable to utilize the limited number of finetuned samples towards data-efficient analytics for survival outcome prediction. The code is available at https://github.com/Cassie07/PathOmics.
Some consequences of thermodynamic feasibility for chemical reaction networks

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One-component ionizable amphiphilic Janus dendrimers as a delivery platform for efficient mRNA vaccine development

There have been rapid advances in nucleoside-modified messenger RNA–based vaccines, particularly during the SARS-CoV-2 pandemic, demonstrating a rapid and cost-effective approach for addressing infectious diseases. A major challenge remains in developing a delivery system that protects mRNA from degradation and facilitates its passage through tissue and cellular barriers. Current four-component lipid nanoparticles enable efficient endosomal escape and are a pivotal technology for the delivery of mRNA vaccines. However, challenges such as stability, availability, durability, and adverse effects persist. We have developed a self-assembling one-component ionizable amphiphilic Janus dendrimers (IAJD) delivery system with naturally occurring amino heads, capable of efficiently delivering mRNA to the spleen and lymph nodes. This single-component system simplifies synthesis, reduces development complexity, and enables rapid global distribution of mRNA vaccines during pandemics. As a proof of concept, one-component IAJD97, formulated with mRNA encoding norovirus mRNA capsid protein, demonstrates the potential of IAJDs as efficient delivery platform for mRNA vaccines, advancing their effectiveness and expanding applications to improve public health outcomes.
Responsible Educational Technology Research: From Open Science and Open Data to Ethics and Trustworthy Learning Analytics

This chapter unfolds some elements of responsible research in the educational technology field and provides examples about how these elements have been considered in initiatives by the Interactive and Distributed Technologies for Education (TIDE) research group at Universitat Pompeu Fabra in Barcelona. First, it focuses on open science, an ongoing movement that promotes, on the one hand, transparent and frequent open-access updates of the research progress and the collected data and, on the other hand, reproducible, accurate, and verifiable research, bringing benefits for the individual researchers, the research community, and the society. Second, the chapter discusses ethics perspectives in educational technology research, relevant when collecting and sharing data and also in the design and development of technologies, especially when they are based on data analytics or artificial intelligence techniques. The latter aspects relate to the capacity of educational software systems to support human agency and preserve human well-being.