ethicalabs/Research-Intent-Collab huggingface dataset:
A procedure for the determination of the rare earth elements, lanthanum through lutetium, in chondritic, achondritic and iron meteorites by neutron-activation analysis

Abstract   The abundances of the rare earths. lanthanum through lutetium, have been determined in chondritic, achondritic, and iron meteorites by neutron-activation analysis. The procedure usud should also be applicable to the analysis of terrestrial stones and sediments. After exposure to a thermal-neutron flux of 2.1012 neutrons/cm2/sec for 2 h, the chondritic or achondritic sample, with added rare earth carriers, is dissolved after sodium peroxide fusion. Iron specimens are dissolved in a hydrochloric acid medium. The rare earths are then separated as a group from the matrix and are individually separated by means of a Dowex 50 W-X12 cation resin column and elution with 1M ammonium lactate. This method is sensitive to fractional parts per million of the individual rare earths. The abundance of scandium may also be determined in the same procedure.
Additional file 1: of Experiences of frontline nursing staff on workplace safety and occupational health hazards in two psychiatric hospitals in Ghana

Questionnaire. Content description of the structured questionnaire used for the data collection. (PDF 72 kb)
Curvature measures for nonlinear regression models using continuous designs with applications to optimal experimental design

We present and illustrate the methodology to calculate curvature measures for continuous designs, and extend design criteria to incorporate continuous designs. These design algorithms include quadratic design procedures, a subset design criterion, a second-order mean-square error design criterion, and a marginal curvature design methodology. A discussion of confidence intervals is also provided for continuous designs.
Exploring the Potential of Apple SensorKit and Digital Phenotyping Data as New Digital Biomarkers for Mental Health Research

The use of digital phenotyping continues to expand across all fields of health. By collecting quantitative data in real-time using devices such as smartphones or smartwatches, researchers and clinicians can develop a profile of a wide range of conditions. Smartphones contain sensors that collect data, such as GPS or accelerometer data, which can inform secondary metrics such as time spent at home, location entropy, or even sleep duration. These metrics, when used as digital biomarkers, are not only used to investigate the relationship between behavior and health symptoms but can also be used to support personalized and preventative care. Successful phenotyping requires consistent long-term collection of relevant and high-quality data. In this paper, we present the potential of newly available, for approved research, opt-in SensorKit sensors on iOS devices in improving the accuracy of digital phenotyping. We collected opt-in sensor data over 1 week from a single person with depression using the open-source mindLAMP app developed by the Division of Digital Psychiatry at Beth Israel Deaconess Medical Center. Five sensors from SensorKit were included. The names of the sensors, as listed in official documentation, include the following: phone usage, messages usage, visits, device usage, and ambient light. We compared data from these five new sensors from SensorKit to our current digital phenotyping data collection sensors to assess similarity and differences in both raw and processed data. We present sample data from all five of these new sensors. We also present sample data from current digital phenotyping sources and compare these data to SensorKit sensors when applicable. SensorKit offers great potential for health research. Many SensorKit sensors improve upon previously accessible features and produce data that appears clinically relevant. SensorKit sensors will likely play a substantial role in digital phenotyping. However, using these data requires advanced health app infrastructure and the ability to securely store high-frequency data.
Parallel Algorithm of SOI Layout Decomposition for Double Patterning Lithography on High-Performance Computer Platforms

In the paper silicon on insulator layout decomposition algorithms for the double patterning lithography on high performance computing platforms are discussed. Our approach is based on the use of a contradiction graph and a modified concurrent breadth-first search algorithm. We evaluate our technique on both real-world and artificial test cases including non-Manhattan geometry. Experimental results show that our soft computing algorithms decompose layout successfully and a minimal distance between polygons in layout is increased.
Digital phenotyping for mental health based on data analytics: A systematic literature review

Even though mental health is a human right, mental disorders still affect millions of people worldwide. Untreated and undertreated mental health conditions may lead to suicide, which generates more than 700,000 deaths annually around the world. The broad adoption of smartphones and wearable devices allowed the recording and analysis of human behaviors in digital devices, which might reveal mental health symptoms. This analysis constitutes digital phenotyping research, referring to frequent and constant measurement of human phenotypes in situ based on data from smartphones and other personal digital devices. Therefore, this article presents a systematic literature review providing a computer science view on data analytics for digital phenotyping in mental health. This study reviewed 5,422 articles from ten academic databases published up to September 2024, generating a final list of 74 studies. The investigated databases are ACM, IEEE Xplore, PsycArticles, PsycInfo, Pubmed, Science Direct, Scopus, Springer, Web of Science, and Wiley. We investigated ten research questions, considering explored data, employed devices, and techniques for data analysis. This review also organizes the application domains and mental health conditions, data analytics techniques, and current research challenges. This study found a growing research interest in digital phenotyping for mental health in recent years. Current approaches still present a high dependence on self-reported measures of mental health status, but there is evidence of the employment of smartphones for leveraging passive data collection. Traditional machine learning techniques are the main explored strategies for analyzing the large amount of collected data. In this regard, published approaches deeply focused on data analysis, generating opportunities concerning the implementation of resources for assisting individuals suffering from mental disorders.
STRAND: Sequence-Conditioned Transport for Single-Cell Perturbations

Predicting how genetic perturbations change cellular state is a core problem for building controllable models of gene regulation. Perturbations targeting the same gene can produce different transcriptional responses depending on their genomic locus, including different transcription start sites and regulatory elements. Gene-level perturbation models collapse these distinct interventions into the same representation.   We introduce STRAND, a generative model that predicts single-cell transcriptional responses by conditioning on regulatory DNA sequence. STRAND represents a perturbation by encoding the sequence at its genomic locus and uses this representation to parameterize a conditional transport process from control to perturbed cell states. Representing perturbations by sequence, rather than by a fixed set of gene identifiers, supports zero-shot inference at loci not seen during training and expands inference-time genomic coverage from ~1.5% for gene-level single-cell foundation models to ~95% of the genome.   We evaluate STRAND on CRISPR perturbation datasets in K562, Jurkat, and RPE1 cells. STRAND improves discrimination scores by up to 33% in low-sample regimes, achieves the best average rank on unseen gene perturbation benchmarks, and improves transfer to novel cell lines by up to 0.14 in Pearson correlation. Ablations isolate the gains to sequence conditioning and transport, and case studies show that STRAND resolves functionally alternative transcription start sites missed by gene-level models.
Ethical tensions between AI surveillance architectures, human rights preservation, and the universal entitlement to digital privacy and dignity

The proliferation of AI-driven surveillance architectures has intensified global debates surrounding privacy, dignity, and the preservation of human rights in digital societies. From a broad perspective, artificial intelligence technologies including facial recognition, behavioral analytics, and predictive policing have become integral to governance, security, and commercial systems. Yet their expansion has also introduced profound ethical tensions between the pursuit of safety and the protection of individual freedoms. States increasingly deploy AI surveillance under the banner of national security and public order, while private corporations utilize similar tools for consumer profiling and behavioral prediction. This convergence of state and corporate monitoring creates unprecedented asymmetries of power over individuals’ digital identities and personal autonomy. At the normative level, these practices challenge the universal entitlement to privacy and dignity enshrined in international human rights law, including the Universal Declaration of Human Rights (Article 12) and the International Covenant on Civil and Political Rights (Article 17). Narrowing the scope, this paper examines how algorithmic surveillance erodes the principles of consent, proportionality, and accountability that underpin digital rights frameworks. It highlights the blurred boundary between legitimate oversight and intrusive control, exploring case studies where AI surveillance has facilitated discrimination, social manipulation, and suppression of dissent. Ultimately, the paper argues that reconciling technological innovation with human rights preservation requires embedding ethical oversight mechanisms into AI governance architectures. Establishing binding safeguards, transparency mandates, and rights-based digital charters is essential to ensuring that security-enhancing technologies do not compromise human dignity. In the evolving digital order, privacy must remain a universal entitlement rather than a privilege subject to algorithmic discretion.
SECOND SEASON QUIET OBSERVATIONS: MEASUREMENTS OF THE COSMIC MICROWAVE BACKGROUND POLARIZATION POWER SPECTRUM AT 95 GHz

The Q/U Imaging ExperimenT (QUIET) has observed the cosmic microwave background (CMB) at 43 and 95 GHz. The 43 GHz results have been published in a previous paper, and here we report the measurement of CMB polarization power spectra using the 95 GHz data. This data set comprises 5337 hr of observations recorded by an array of 84 polarized coherent receivers with a total array sensitivity of 87 μK. Four low-foreground fields were observed, covering a total of 1000 deg2 with an effective angular resolution of 128, allowing for constraints on primordial gravitational waves and high signal-to-noise measurements of the E-modes across three acoustic peaks. The data reduction was performed using two independent analysis pipelines, one based on a pseudo-C ℓ (PCL) cross-correlation approach, and the other on a maximum-likelihood (ML) approach. All data selection criteria and filters were modified until a predefined set of null tests had been satisfied before inspecting any non-null power spectrum. The results derived by the two pipelines are in good agreement. We characterize the EE, EB, and BB power spectra between ℓ = 25 and 975 and find that the EE spectrum is consistent with ΛCDM, while the BB power spectrum is consistent with zero. Based on these measurements, we constrain the tensor-to-scalar ratio to r = 1.1+0.9 -0.8 (r &lt;2.8 at 95% C.L.) as derived by the ML pipeline, and r = 1.2+0.9 - 0.8 (r &lt;2.7 at 95% C.L.) as derived by the PCL pipeline. In one of the fields, we find a correlation with the dust component of the Planck Sky Model, though the corresponding excess power is small compared to statistical errors. Finally, we derive limits on all known systematic errors, and demonstrate that these correspond to a tensor-to-scalar ratio smaller than r = 0.01, the lowest level yet reported in the literature. © 2012. The American Astronomical Society. All rights reserved..
A Nationwide Survey of Quality of End-of-Life Cancer Care in Designated Cancer Centers, Inpatient Palliative Care Units, and Home Hospices in Japan: The J-HOPE Study

End-of-life (EOL) cancer care in general hospitals and home care has not previously been evaluated in Japan.This study aimed to evaluate EOL cancer care from the perspective of bereaved family members in nationwide designated cancer centers, inpatient palliative care units (PCUs), and home hospices in Japan.We conducted a cross-sectional, anonymous, self-report questionnaire survey for bereaved family members of cancer patients in March 2008 for 56 designated cancer centers and in June 2007 for 100 PCUs and 14 home hospices. Outcomes were overall care satisfaction, structure and process of care (Care Evaluation Scale), and achievement of a good death (Good Death Inventory).In designated cancer centers, PCUs, and home hospices, 2794 (response rate 59%), 5312 (response rate 69%), and 292 (response rate 67%) bereaved family members participated, respectively. Mean scores for overall care satisfaction were high for all places of death, at 4.3 ± 1.2 for designated cancer centers, 5.0 ± 1.2 for PCUs, and 5.0 ± 1.0 for home hospices. Designated cancer centers showed significantly lower ratings than PCUs and home hospices for structure and process of care and achievement of a good death (P = 0.0001 each). Home hospices were rated significantly higher than PCUs for achievement of a good death (P = 0.0001).The main findings of this study were: (1) overall, bereaved family members were satisfied with end-of-life care in all three places of death; (2) designated cancer centers were inferior to PCUs and home hospices and had more room for improvement; and 3) home hospices were rated higher than PCUs for achieving a good death, although home hospices remain uncommon in Japan.
A Brief Review of Machine Learning and Its Application

With the popularization of information and the establishment of the databases in great number, and how to extract data from the useful information is the urgent problem to be solved. Machine learning is the core issue of artificial intelligence research, this paper introduces the definition of machine learning and its basic structure, and describes a variety of machine learning methods, including rote learning, inductive learning, analogy learning , explained learning, learning based on neural network and knowledge discovery and so on. This paper also brings foreword the objectives of machine learning, and points out the development trend of machine learning. Keywords-machine learning; intelligence; methods; application
Methodological and ethical aspects of randomized controlled clinical trials in minors with malignant diseases

AbstractBackgroundDue to the new European regulations for pediatric medications, future clinical trials will include an increasing number of minors. It is therefore important to reconsider and evaluate recent methodological and ethical aspects of clinical trials in minors.ProcedureThe following questions were investigated: How are randomized controlled clinical trials (RCTs) performed in practice? Do investigators take into consideration biomedical ethical principles, explicated for example by Beauchamp and Childress, when planning and conducting a trial? The study was conducted in a descriptive manner. A systematic, algorithm‐guided search focusing on RCTs in minors with malignant diseases was carried out in PubMed. One‐thousand‐nine‐hundred‐sixty‐two publications from 2001 to 2005 were randomized in sequence. The first 1,000 publications were screened according to a priori defined inclusion criteria. One hundred seventy‐five publications met the criteria and were reviewed using the SIGN methodological checklist (2004), the CONSORT Statement (2001, section Methods, items 3–12) and indicators for ethical aspects. Seventeen publications were checked by two raters.ResultsInformation on randomization and blinding was often equivocal. The publications were mainly rated positive for the criteria of the SIGN checklist, and mostly rated negative for the additional items of the CONSORT Statement. Regarding the ethical principles, only few contributions were found in the publications. Inter‐rater reliability was good.ConclusionsIn the publications analyzed, we found only limited information concerning methods and reflections on ethical principles of the trials. Improvements are thus necessary and possible. We suggest how such trials and their respective publications can be optimized for these aspects. Pediatr Blood Cancer 2011; 57: 599–605. © 2011 Wiley‐Liss, Inc.
White Privilege and the Decolonization Work Needed in Evaluation to Support Indigenous Sovereignty and Self-Determination

Abstract: This paper builds on a keynote paper presented at the 2018 Canadian Evaluation Society annual conference by Kate McKegg, a Pākehā, non-Indigenous evaluator from Aotearoa, New Zealand. Kate reflects on the concept and implications for Indigenous people of white privilege in colonized Western nations. She discusses some of the ways in which white privilege and its consequences play out in the field of evaluation, perpetuating colonial sentiments and practices that maintain and reinforce inequities and injustice and potentially threaten the social justice aspirations of the field. Kate argues that those with white privilege have much work to do, unpacking and understanding their privilege if they are to have any chance of playing a role in deconstructing and dismantling the power structures that hold colonizing systems in place. She suggests that for evaluators to be effective allies for Indigenous sovereignty and self-determination, they must undertake ideological, cultural, emotional, and constitutional work. This work will be tough and scary and is not for the faint hearted. But it is vital to unlocking the potential transformation that can come from just and peaceful relationships that affirm and validate Indigenous peoples' ways of knowing and being.
The Transformation of Sovereignty After the NATO Intervention: From Humanitarian Intervention to the 'Responsibility to Protect'

NATO's intervention in former Yugoslavia had a profound impact on the principle of sovereignty in International Relations. It challenged the conventional understanding of sovereignty as the absolute right of a state to exercise its internal authority without external interference from other states or the international community. The debate in international relations sparked by NATO's intervention shifted from the right of states to intervene to the international community's responsibility to protect civilians from ethnic cleansing and mass atrocities in any given state.  The humanitarian intervention in Kosovo served as a turning point in this regard. Despite lacking a legal basis in international law—a clear mandate from the UN Security Council—it was proven to be entirely legitimate because the situation in Kosovo had escalated into a genuine humanitarian crisis, with the threat of genocide evident. Furthermore, this case spurred debate in international law, particularly in affirming the responsibility to protect and redefining the limitations of non-intervention when a state fails to protect its citizens.  With the adoption of UN Security Council Resolution 1973 authorizing humanitarian intervention in Libya, the international community solidified this affirmative development that had begun with NATO's intervention. This marked a paradigmatic shift, as it not only challenged the constraints imposed by the principle of non-intervention in internal affairs but also created the preconditions for the establishment of the principle known as the “responsibility to protect.” Moreover, it strengthened stability, peace, and the respect for human rights in the region and beyond.
Past Disruptions in Health Insurance Coverage and Access to Care Among Insured Adults

Although the association between health insurance coverage and access to care is well documented, it is unclear whether the deleterious effects of being uninsured are strictly contemporaneous or whether previous disruptions in coverage have persistent effects. This study addresses this issue using nationally representative data covering 2011-2019 to estimate the extent to which disruptions in health insurance coverage continued to be associated with poor access even after coverage was regained.Analysis was conducted in 2022. Using a nationally representative cohort of insured adults aged 18-64 years (N=39,904) and multivariable logistic regression models, the authors estimated the association between past disruptions in coverage (occurring at least 1 year before) and the risks of lacking a usual source of care provider and having unmet medical need.Among insured nonelderly adults, the risk of being without a usual source of care provider was between 18% (risk ratio=1.18; 95% CI=1.00, 1.38) and 75% higher (risk ratio=1.75; 95% CI=1.56, 1.93) than for those with continuous coverage; the risk of having unmet medical needs was between 41% (risk ratio=1.41; 95% CI=1.00, 1.83) and 66% (risk ratio=1.66; 95% CI=1.26, 2.06) higher. Longer insurance disruptions were associated with a higher risk of lacking a usual source of care provider.Previous disruptions in health insurance coverage continued to be negatively associated with access to care for more than a year after coverage was regained. Improving access to care in the U.S. may require investing in policies and programs that help to strengthen coverage continuity among individuals with insurance coverage rather than focusing exclusively on helping uninsured individuals to gain coverage.
Quantum Random Self-Modifiable Computation

Among the fundamental questions in computer science, at least two have a deep impact on mathematics. What can computation compute? How many steps does a computation require to solve an instance of the 3-SAT problem? Our work addresses the first question, by introducing a new model called the ex-machine. The ex-machine executes Turing machine instructions and two special types of instructions. Quantum random instructions are physically realizable with a quantum random number generator. Meta instructions can add new states and add new instructions to the ex-machine. A countable set of ex-machines is constructed, each with a finite number of states and instructions; each ex-machine can compute a Turing incomputable language, whenever the quantum randomness measurements behave like unbiased Bernoulli trials. In 1936, Alan Turing posed the halting problem for Turing machines and proved that this problem is unsolvable for Turing machines. Consider an enumeration E_a(i) = (M_i, T_i) of all Turing machines M_i and initial tapes T_i. Does there exist an ex-machine X that has at least one evolutionary path X --> X_1 --> X_2 --> . . . --> X_m, so at the mth stage ex-machine X_m can correctly determine for 0 <= i <= m whether M_i's execution on tape T_i eventually halts? We demonstrate an ex-machine Q(x) that has one such evolutionary path. The existence of this evolutionary path suggests that David Hilbert was not misguided to propose in 1900 that mathematicians search for finite processes to help construct mathematical proofs. Our refinement is that we cannot use a fixed computer program that behaves according to a fixed set of mechanical rules. We must pursue methods that exploit randomness and self-modification so that the complexity of the program can increase as it computes.