ethicalabs/Research-Intent-Collab huggingface dataset:
Balancing Innovation, Biosecurity, and Biosafety in Dual-Use Research in the Middle East

Dual-use research is known for its double use, contributing to positive advancements and serious risks, especially in regions with political instability and low biosafety and biosecurity protocols. This paper offers background knowledge, regional challenges, and much more regarding the situation in the Middle East. Case studies highlight regional regulations' effectiveness and the consequences of not following them by comparing biosafety and biosecurity practices in the Middle East with global standards. We concluded with multiple points on how Regional and international cooperation are essential for sharing the region's information and policy alignment, with recommendations to improve the regulatory frameworks and financing lab facilities and to increase awareness of bioethics and dual-use concerns by educational and training initiatives. This review aims to help researchers and policymakers create a more secure and accountable scientific environment in the region; by filling these directed gaps, we aim to enhance the integrity of Middle East research and biosecurity.
Initial Conditions of Planet Formation: Time Constraints from Small Bodies and the Lifetime of Reservoirs in the Solar Protoplanetary Disk

This review explores the timescales of the initial phase of planet formation, from nebular dust (CAIs and chondrules) to planetesimal accretion and differentiation, using evidence from meteorite research. Aluminium-Mg systematics of CAIs indicate either an extended period of CAI formation (∼0.3 Ma) or an initial 26Al heterogeneity, with evidence supporting a homogeneous 26Al abundance in the protoplanetary disk. Thermal and aqueous alteration on the parent body can disturb the U-Pb and Al-Mg chronometers in chondrules. Focusing on relatively robust isochron data from plagioclase of pristine (types ≤3.05) chondrites indicates a shift in chondrule formation locations, moving from the inner to the outer disk over time. Ages of basaltic achondrites show that silicate differentiation on small bodies was well underway within the first few million years (Ma) of our solar system. Their age record, however, reveals inconsistencies between different chronometers, partly caused by (i) secondary disturbances due to thermal metamorphism, aqueous alteration, or impacts, (ii) the presence of xenolithic minerals, and (iii) potentially variable initial 26Al abundances due to disturbances at the mineral scale. Nucleosynthetic isotope data indicate that parent bodies of iron and stony meteorites formed in two distinct regions within the protoplanetary disk: the inner, non-carbonaceous (NC) and the outer, carbonaceous (CC) region. Based on Hf-W chronometry it has been demonstrated that NC and CC parent bodies of magmatic iron meteorites segregated their cores within ∼1–3 Ma after CAI formation, implying that parent body accretion occurred within &lt;1 Ma in both reservoirs. Combining accretion ages with nucleosynthetic data further reveals that, at first order, NC and CC reservoirs in the solar protoplanetary disk were established within 1 Ma and existed over several Ma with limited exchange between them. In the CR chondrite accretion region of the disk, planetary bodies formed over at least 3 Ma, while in most other regions, formation spanned at least 1 Ma, with minimal changes in nucleosynthetic isotope compositions. Aerodynamical size sorting of dust likely introduced or amplified some of these variations.
Comparing Molecules Generated by MMPDB and REINVENT4 with Ideas from Drug Discovery Design Teams

This study compares molecules designed by drug discovery project teams from the Sanders Tri-Institutional Therapeutics Discovery Institute with molecules generated by two computational tools: MMPDB and REINVENT4. Seven different test cases with diverse chemotypes are studied in order to explore the potential of these computational tools in complementing human expertise in the early stages of drug discovery. By comparing the molecular structures and properties generated by MMPDB and REINVENT4 to those designed by project design teams, we aim to assess the value of such tools. The results indicate that MMPDB and REINVENT4 cover regions of chemical space larger than those covered by ideas from the drug discovery project teams. However, the chemical spaces covered by the two methods are quite different, and neither method completely covers the chemical space identified by the drug discovery project teams. Thus, the computational methods are complementary to one another and to drug discovery project team ideation. Effective application of generative molecule design tools has the potential to accelerate the identification of novel therapeutic candidates by expanding the chemical space explored during drug discovery and enabling optimal exploration.
AlphaFold as a Prior: Guiding Protein Structure Prediction Using Experimental Data with ROCKET

Advances in machine learning have transformed structural biology, enabling swift and accurate prediction of protein structure from sequence. However, challenges persist in capturing sidechain packing, condition-dependent conformational dynamics, and biomolecular interactions, primarily due to scarcity of high-quality training data. Emerging techniques, including cryo-electron tomography (cryo-ET) and high-throughput crystallography, promise vast new sources of structural data, but translating experimental observations into mechanistically interpretable atomic models remains a key bottleneck. Here, we address these challenges by improving the efficiency of structural analysis through combining experimental measurements with a landmark protein structure prediction method – AlphaFold2. We present an augmentation of AlphaFold2, ROCKET, that refines its predictions using cryo-EM, cryo-ET, and X-ray crystallography data, and demonstrate that this approach captures biologically important structural variation that AlphaFold2 does not. By performing structure optimization in the space of coevolutionary embeddings, rather than Cartesian coordinates, ROCKET automates difficult modeling tasks, such as flips of functional loops and domain rearrangements at low resolution. ROCKET does not require retraining of AlphaFold2 and is readily adaptable to other data modalities. This new type of structure refinement that optimizes latent representations in evolutionary space could unlock possibilities for high-throughput ligand screening, assemblies solved at low resolution, and conformational landscapes.
Identification of Gamma Ultra High Energy Cosmic Rays by Simulating Extensive Air Showers

Among the most interesting tasks for the identification of Ultra High Energy Cosmic Rays (origin, mechanisms of acceleration, top down model, direction, and maximum energy) is their isotopic composition. For example, if they are protons, heavier nuclei, gammas or even exotic. Air Shower Extended Simulation code (AIRES) is used to simulate the Extended Atmospheric Showers. This code gives, among others, the maximum number of secondary particles within the atmosphere along the longitudinal direction of the showers. From the distribution of the depths of maximum number of shower particles and their content in muons, we can distinguish between proton and gamma primary cosmic rays, both of energy of 100 EeV. The results show a maximum at lower atmospheric depths for protons and at higher for gammas, respectively. Due to the bremsstrahlung and pair production effects, the muon content of gamma showers is much poorer than of protons. Both facts enable the distinction between proton and gamma cosmic rays. For the simulation of the atmospheric EAS due to the passage of an Ultra High Energy Cosmic Ray, the Linsley standard atmospheric model is used.
Quality of end-of-life care in patients with hematological malignancies: potential role of palliative care

Limited data are available on the impact of specialist palliative care on end-of-life care quality for patients with hematologic malignancies. This study aims to analyze the quality of end-of-life care in patients with hematological malignancies, comparing those who receive palliative care with those who do not.Observational, single center retrospective study. This study was conducted at the National Cancer Institute (INCan) in Mexico City, a tertiary care hospital, between January 2016 and June 2021. This study included deceased patients with hematological malignancies who were hospitalized or patients who were hospitalized and receiving home palliative care, with follow-up from the palliative care service. End-of-life care quality was assessed using the ASCO/NQF instrument.Three hundred sixty deceased patients with hematological malignancies were included in the analysis; 51.4% were men, with a median age of 52 years. The most common diagnosis was non-Hodgkin lymphoma (41.4%); 37.8% of patients were referred to palliative care, with an average referral time from admission to INCan of 99.5 days. Patients without palliative care referral showed worse quality of death indicators (71.6% vs. 28.4%). Survival analysis revealed a median survival of 5.29 months for patients with up to 3 worse quality of death indicators and 3.65 months for those with ≥ 4 worse quality of death indicators at the end-of-life (p < 0.001).Patients with hematologic malignancies who did not receive palliative care experienced more intensive end-of-life interventions and had lower overall survival rates. Early integration of palliative care is crucial to promote compassionate approaches near death and ensure quality end-of-life care.
Deep Reinforcement Learning-Based Semi-Autonomous Control for Magnetic Micro-Robot Navigation with Immersive Manipulation

Accepted by ICRA
Supplementary document for PMONN: an optical neural network for photonic integrated circuits based on micro-resonator - 6794139.pdf

The supplemental materials of the paper
A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception

Optical microrobots, manipulated via optical tweezers (OT), have broad applications in biomedicine. However, reliable pose and depth perception remain fundamental challenges due to the transparent or low-contrast nature of the microrobots, as well as the noisy and dynamic conditions of the microscale environments in which they operate. An open dataset is crucial for enabling reproducible research, facilitating benchmarking, and accelerating the development of perception models tailored to microscale challenges. Standardised evaluation enables consistent comparison across algorithms, ensuring objective benchmarking and facilitating reproducible research. Here, we introduce the OpTical MicroRobot dataset (OTMR), the first publicly available dataset designed to support microrobot perception under the optical microscope. OTMR contains 232,881 images spanning 18 microrobot types and 176 distinct poses. We benchmarked the performance of eight deep learning models, including architectures derived via neural architecture search (NAS), on two key tasks: pose classification and depth regression. Results indicated that Vision Transformer (ViT) achieve the highest accuracy in pose classification, while depth regression benefits from deeper architectures. Additionally, increasing the size of the training dataset leads to substantial improvements across both tasks, highlighting OTMR's potential as a foundational resource for robust and generalisable microrobot perception in complex microscale environments.
Artificial Intelligence in Intelligence Agencies, Defense and National Security

This book explores the use of artificial intelligence by intelligence services around the world and its critical role in intelligence analysis, defense, and national security. Intelligence services play a crucial role in national security, and the adoption of artificial intelligence technologies has had a significant impact on their operations. It also examines the various applications of artificial intelligence in intelligence services, the implications, challenges and ethical considerations associated with its use. The book emphasizes the need for continued research and development in the field of artificial intelligence to ensure that intelligence services. and overall national defense and security can effectively adapt to emerging threats.
Giving Back: Return of Results Reports Using Digital Phenotyping Tools in Mental Health

Abstract                 As digital phenotyping tools become more prevalent in mental health research and care, the question of how to meaningfully return data to participants, clinicians, and caregivers has grown increasingly important. Drawing from the broader DeeP-DD (Deep Phenotyping and Digitalization at the Douglas) project, this work presents the iterative development of individualized feedback reports focused on a psychiatric patient population. This paper also builds on findings from a narrative literature review to derive evidence-based practices around conveying data to participants. From the literature review, general themes such as patient engagement, visual design, ethical considerations and report content were extracted. Core design principles identified included visual simplicity, use of color, contextualized interpretation, and ethical considerations, which were compiled and helped guide the presentation of data gathered from participants in user-friendly formats. The reports created from these findings are based on both digital and clinical data, and their design was informed by key findings from the narrative review and developed through a participatory process involving patients, clinicians, and caregivers. Findings from early user feedback and existing literature suggest that well-designed reports can foster greater understanding, trust, and behavioral engagement in research and clinical care. The review also highlights important gaps, particularly in caregiver-focused communication, and discusses future directions including developing similar reports for both physicians and caregivers and the use of digital report platforms. By addressing both design and ethical considerations in a real-world setting, this work contributes to the field of return-of-results practices in psychiatric digital health.
Bridging education and research to investigate biodegradable packaging materials’ impact on aquatic health: A citizen science approach

The environmental impact of biodegradable and compostable packaging materials on aquatic ecosystems’ health remains critically understudied. To address this gap, the ‘CiDIA-micro’ project engages 111 high school students and 7 teachers, 9 researchers, and 3 universities in a collaborative citizen science initiative within EURECA-PRO ‘The European University on Responsible Consumption and Production’. The project investigates the ecotoxicological effects of biodegradable packaging materials on diatom algae, which serve as key bioindicators of water quality. By integrating experimental research into classrooms, the initiative fosters meaningful learning and develops green competences for sustainability, environmental stewardship, and scientific inquiry, while generating valuable data for ecological research.Experimental microcosms simulating aquatic environments and climate change conditions were established in six high schools in León province and at university laboratories. Participants received hands-on training in diatom sampling, environmental monitoring, and research methodologies. Monthly assessments evaluate diatom population growth, community composition, ecophysiology, and teratologies, alongside water quality analysis. Advanced chemical and physical analyses of the packaging materials pre- and postexposure investigate heavy metal release, microplastic generation, and material degradation.Preliminary findings reveal significant interactions between biodegradable packaging materials and aquatic ecosystems, raising concerns about heavy metal additives and microplastic fragmentation. By aligning with SDG12 and EU regulatory standards, this project provides key insights to inform packaging policy and promote a circular economy. Additionally, the initiative demonstrates the power of citizen science in uniting education, research, and community engagement, offering a scalable model for fostering meaningful learning and equipping participants with green competences to address sustainability challenges.
An Analysis of Internal Business Management and Ethical Issues of Uber in the UK—Based on Utilitarianism, Deontology and Corporate Social Responsibility

This paper delves into the ethical issues surrounding Uber Technologies Inc., a multinational transportation services company, with a particular focus on its private car hire business in the United Kingdom. The analysis is grounded in three ethical frameworks: utilitarianism, deontology, and corporate social responsibility. The paper begins by acknowledging the widespread adoption of Uber's services in the UK, highlighting its rapid growth and the controversies that have accompanied it.The paper first identifies the primary ethical issue arising from Uber's dominance in the ground transportation market. From a utilitarian perspective, Uber's expansion is deemed ethical as it enhances the overall happiness of the community by providing flexible work opportunities for millions and safer transportation services to passengers. However, this expansion has come at the cost of taxi drivers, who have lost business and face an unfair competitive landscape.The analysis then shifts to a deontological perspective, which emphasizes the importance of fair competition and adherence to categorical imperatives. Corporate social responsibility (CSR) is the third ethical framework employed in this analysis. The paper underscores Uber's responsibility to maintain the social structure and ensure the well-being of all stakeholders. This paper provides a comprehensive analysis of the ethical issues associated with Uber's private car hire business in the UK, drawing on utilitarianism, deontology, and corporate social responsibility. It highlights the challenges faced by the company in balancing its growth with ethical considerations and offers recommendations for future action.
Limit theory of combinatorial optimization for random geometric graphs

64 pages
Microbial Based 'Cradle-to-Cradle' Approach to Attain Sustainable  Development Goals of Food and Water Security, Good Health and Well  Being without Crossing the Planetary Boundaries

Our planet is facing a wide range of inevitable and unprecedented changes such as, the water and food scarcity to the natural calamities, namely flooding, droughts and rising sea levels. All these global challenges had been addressed through the Sustainable Development Goals (SDGs) drafted by the general assembly of the United Nations. In light of the current population growth, it is difficult to attain the sustainable development using conventional and non-renewable natural resources by remaining within the planetary boundaries of Earth. In order to maintain the environment and ecological integrity, the utilization of renewable living natural resources such as microbes become inevitable. Due to their roles in geo physio-chemical processes and bioenergy transformations, microbes allow 'cradle-to-cradle' model of development using wastewater as a renewable resource. The circular wastewater economy is the sole sustainable method to achieve the SDGs of providing clean water and the sanitation to address the issue of water insecurity. The review presents an inter-connected overview on the roles and functions performed by the prokaryotic (bacteria) and eukaryotic (algae and fungi) microorganisms, which are crucial for attaining the environment sustainability within the planetary boundaries. Apart from the environmental roles of microbes, the review also highlights the importance of human-microbe interactions (gut microbiome) and edible microbial species (algae and fungi) which are essential for developing sustainable future alternatives to human nutrition, well being and prevention of diseases.
Study of the Vulnerability of Basic Social Infrastructure of the Mexico’s North Border for Purposes of Resiliency and Adaptation to the Adverse Effects of Climate Change

The infrastructure to deliver public services represents the backbone of global society and its development since local climate change official documents consider as strategic the basic social infrastructure for primary networks related to the provision of water, energy, transport and communications. This represents a good opportunity to approach the increasing weather-climate risks to the social infrastructure projects. On the other hand, according to the World Bank it has decreased the amount of life loss due to natural hazards and disasters, but in contrast, each decade the population increases, thus affecting in their belongings and the social infrastructure exposed to the danger of the climate. Related to the above and taking into account the commitments and aspirations in the field of climate change in Mexico, we proposed a research project in our universities related to vulnerability of the basic social infrastructure of Mexico´s north border, for purposes of resilience and adaptation to the adverse effects of climate change. The general project aim is to identify and classify the basic social infrastructure at the north border States of the Country related to the socio-economic and biophysical vulnerability (climate change impacts) to suggest adaptation and resilience measures. These paper aims to expose the results of these initiative and points out some opportunities for university students and the incorporation of the variable climate change in major projects, including the National Infrastructure Program that worth 600 billion dollars.
Association between Consultation by a Comprehensive Integrated Palliative Care Program and Quality of End-of-Life Care in Patients with Advanced Cancer in Edmonton, Canada

Literature assessing the impact of palliative care (PC) consultation on aggressive care at the end of life (EOL) within a comprehensive integrated PC program is limited. We retrospectively reviewed patients with advanced cancer who received oncological care at a Canadian tertiary center, died between April 2013 and March 2014, and had access to PC consultation in all healthcare settings. Administrative databases were linked, and medical records reviewed. Composite score for aggressive EOL care was calculated, assigning a point for each of the following: ≥2 emergency room visits, ≥2 hospitalizations, hospitalization &gt;14 days, ICU admission, and chemotherapy administration in the last 30 days of life, and hospital death. Multivariable logistic regression was adjusted for age, sex, income, cancer type and PC consultation for ≥1 aggressive EOL care indicator. Of 1414 eligible patients, 1111 (78.6%) received PC consultation. In multivariable analysis, PC consultation was independently associated with lower odds of ≥1 aggressive EOL care indicator (OR 0.49, 95% CI 0.38–0.65, p &lt; 0.001). PC consultation &gt;3 versus ≤3 months before death had a greater effect on lower aggressive EOL care (mean composite score 0.59 versus 0.88, p &lt; 0.001). We add evidence that PC consultation is associated with less aggressive care at the EOL for patients with advanced cancer.