ethicalabs/Research-Intent-Collab huggingface dataset:
A LAVA FLOW SIMULATION EXPERIENCE ORIENTED TO DISASTER RISK REDUCTION, EARLY WARNING SYSTEMS AND RESPONSE DURING THE 2021 VOLCANIC ERUPTION IN CUMBRE VIEJA, LA PALMA.

Lava flows are one of the hazards involved in a volcanic eruption, and although they rarely cause the loss of human life, they are highly destructive in terms of damage to property and economic activity. Therefore, the management of volcanic disasters requires fast and accurate information on the behaviour and evolution of the flows, mainly related to their extension, displacement, and trajectory. This was the case during the disaster linked to the volcanic event that occurred on the island of La Palma in the Cumbre Vieja area at the end of 2021, which lasted eighty-five days. This paper describes part of the work performed by many different groups to provide predictive information aimed at feeding the early warning system set up during the disaster. This case shows the experience in the use of a probabilistic simulation algorithm implemented in the Q-LavHA plugin for the QGIS software, which is both easily accessible and applicable, to analyze its features in detail, as well as its predictive capacity. The results show that the model can efficiently and quickly satisfy the demand for this type of information, and its high similarity value is also validated by the Kappa index.
Quantum computations: algorithms and error correction

Summary: The first part of the article is devoted mainly to one goal, namely, to showing the computational capacity of a quantum computer using the problem of a stabilizer in the group \(\mathbb{Z}^k\) as an example. The discrete logarithm and decomposition into prime factors can be reduced to this problem. The formal definition of a quantum computer (more precisely, a quantum scheme) appears in \S 4. All necessary information from computing theory and quantum mechanics is contained in \S 2 and \S 3. The reading of the second part can begin with the theory of one-to-one quantum codes. This theory is sufficiently complete, simple and self-contained. However, in the present paper it is considered as a means of solving the perturbation problem, that is, constructing a quantum computer from unreliable (inaccurate, being subject to perturbations) elements. The rest is a rather tedious technical preparation. (So far the problem in hand has been considered only at the physical level of rigour. The formal approach revealed one subtle point where a naive argument may lead to an error. The initial formulation of the problem is not rigorous and rests on an intuitive picture of the way a real-world computational device might work.
Neuroscience informed risk assessment and management in forensic mental healthcare: a qualitative analysis of ethical and legal challenges and practice-oriented recommendations

Risk assessment for determining the risk for recidivism in offenders, is a core task within forensic mental healthcare. While current tools predict recidivism with 65–75% accuracy, emerging research suggests that neurobiological factors may enhance predictive validity and aid in treatment response and risk management. Yet, translation into forensic mental health practice stays limited. This study explores the ethical and legal considerations of integrating neurotechnology, specifically neuroprediction and neuromodulation, into forensic mental healthcare. A structured conceptual frameworkis provided as input for the qualitative focus group study (                     N                      = 16) involving professionals and experts by experience. The focus groups revealed a complex interplay between human rights, normative principles, and practical concerns. Key themes include mental integrity, privacy, stigmatization, and informed consent. Participants emphasized the need for contextual interpretation of neural data and transparent communication with clients when neurotechnology, including neural data is used. The findings support cautious optimism for the role of neurotechnology in forensic care, contingent on further research and interdisciplinary dialogue.
Study of Characteristic Properties of Gravitational Waves &amp; it’s Detection using Einstein’s General Theory of Relativity &amp; Laser Interferometer Gravitational Wave Observatory (LIGO)

In this research paper, we have investigated the dependence of power radiated, energy flux and chirp mass of gravitational waves on binary system and orbital decay in the space by applying the Einstein General theory of relativity based on gravitational wave detection technique. The direct detection of gravitational waves, predicted by Einstein’s theory of General Relativity, marks a revolutionary advancement in our understanding of the universe. The core of this research paper examines the mechanics of Laser interferometry used by LIGO to detect these minuscule distortions in space time caused by cataclysmic astrophysical events such as binary black hole mergers and neutron star collisions. It is found that for lower values of chirp mass, the decay rate is significantly less pronounced, suggesting that systems with lower masses will experience slower orbital decay. Conversely, higher chirp masses lead to more rapid decay, which is critical in the context of observable gravitational waves, especially for massive binary systems like black hole mergers. It has also been observed that the higher chirp masses lead to more rapid decay, which is critical in the context of observable gravitational waves, especially for massive binary systems like black hole mergers. This research also analyzes that how gravitational waves effect other celestial bodies and also after merging or colliding what will going to the dynamics of that celestial bodies.
Quality Attributes Optimization of Software Architecture: Research Challenges and Directions

The estimation and improvement of quality attributes in software architectures is a challenging and time-consuming activity. On modern software applications, a model-based representation is crucial to face the complexity of such activity. One main challenge is that the improvement of distinctive quality attributes may require contrasting refactoring actions on the architecture, for instance when looking for trade-off between performance and reliability (or other non-functional quality attributes). In such cases, multi-objective optimization can provide the designer with a more complete view on these trade-offs and, consequently, can lead to identify suitable refactoring actions that take into account independent or even competing objectives.   In this paper, we present open challenges and research directions to fill current gaps in the context of multi-objective software architecture optimization.
Arithmetic Average Density Fusion -- Part I: Some Statistic and Information-theoretic Results

Finite mixture such as the Gaussian mixture is a flexible and powerful probabilistic modeling tool for representing the multimodal distribution widely involved in many estimation and learning problems. The core of it is representing the target distribution by the arithmetic average (AA) of a finite number of sub-distributions which constitute a mixture. While the mixture has been widely used for single sensor filter design, it is only recent that the AA fusion demonstrates compelling performance for multi-sensor filter design. In this paper, some statistic and information-theoretic results are given on the covariance consistency, mean square error, mode-preservation capacity, and the information divergence of the AA fusion approach. In particular, based on the concept of conservative fusion, the relationship of the AA fusion with the existing conservative fusion approaches such as covariance union and covariance intersection is exposed. A suboptimal weighting approach has been proposed, which jointly with the best mixture-fit property of the AA fusion leads to a max-min optimization problem. Linear Gaussian models are considered for algorithm illustration and simulation comparison, resulting in the first-ever AA fusion-based multi-sensor Kalman filter.
Designing mm-wave electromagnetic engineered surfaces using generative adversarial networks

In this paper, we investigate the capability of generative adversarial networks, including conditional and conditional convolutional generative adversarial networks, in generating electromagnetic engineered surfaces (EES). Generative models such as generative adversarial networks and their conditional variants can be used to generate different categories of designs based on the current dataset. k-means clustering algorithm is used to obtain the desirable categories of EES designs, including an initial two main categories, followed by six and eight subcategories. Conditional and conditional convolutional generative adversarial networks are proposed and trained on designs with different image dimensions conditioned on different sets of categories. The trained conditional convolutional generative adversarial network models have comparable accuracy with conditional generative adversarial network in low-dimensional designs over two categories. Conditional convolutional generative adversarial networks generate more unique designs for six and eight categories for smaller image dimensions (e.g., 9 × 9 designs) and for two main categories over larger designs. Both generative adversarial network structures are suitable for generating a wide variety of low- and high-pass EES designs. The creation of new datasets can benefit from conditional convolutional generative adversarial networks to provide greater variety in designs.
Social Value Alignment in Large Language Models

Large Language Models (LLMs) have demonstrated remarkable proficiency in text generation and display an apparent understanding of both physical and social aspects of the world. In this study, we look into the capabilities of LLMs to generate responses that align with human values. We focus on five prominent LLMs - GPT-3, GPT-4, PaLM-2, LLaMA-2 and BLOOM - and compare their generated responses with those provided by human participants. To evaluate the value alignment of LLMs, we presented domestic scenarios to the model and elicited a response with minimal prompting instructions. Human raters judged the responses on appropriateness and value alignment. The results revealed that GPT-3, 4 and PaLM-2 performed on par with human participants, displaying a notable level of value alignment in their generated responses. However, LLaMA-2 and BLOOM fell short in this aspect, indicating a possible divergence from human values. Furthermore, our findings indicate that the raters faced difficulty in distinguishing between responses generated by LLMs and those by humans, with raters exhibiting a preference for machine-generated responses in certain cases. These findings shed light on the capabilities of state-of-the-art LLMs to align with human values, but also allow us to speculate on whether these models could be value-aware. This research contributes to the ongoing exploration of LLMs' understanding of ethical considerations and provides insights into their potential for engaging in value-driven interactions.
Projected changes in precipitation variability over Europe in CMIP6 climate models

Changes in the amount, intensity, frequency and type of precipitation are observed in some places over recent decades (IPCC 2021). While much effort has been devoted to analyzing long-term changes in mean values and extremes, studies on changes in precipitation variability have been rather scarce. Long-term changes in climate variability are, nevertheless, an important aspect of the climate change with various impacts on society and environment. Therefore it is necessary to know whether and how the precipitation variability will change in the future. To this end, it is important that it is simulated correctly by recent climate models. In our study, we analyze outputs from an ensemble of different CMIP6 global climate models and several reanalyses and gridded observed datasets. We study long-term changes in day-to-day precipitation variability and how they differ between various datasets for the historical and current climate. We evaluate how successful the climate models are in reproducing precipitation variability, while identifying biases and errors common to all models or to groups of models. We analyze projected changes of short-term precipitation variability in model simulations over the whole 21st century. We focus on the North Atlantic-European sector. We consider wet-to-wet and dry-to-dry transition probabilities as a measure of short-term precipitation variability, focusing on winter and summer seasons separately.&amp;#160;Ref.: IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. P&amp;#233;an, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelek&amp;#231;i, R. Yu, and B. Zhou (eds.)].
Adopting and adapting clinical practice guidelines for timing of decompressive surgery in acute spinal cord injury from a developed world context to a developing region

The proper application of high-quality clinical practice guidelines improves trauma patients' care and outcomes. This study aimed to adopt and adapt guidelines on the timing of decompressive surgery in acute spinal cord injury (SCI) in Iranian clinical settings.This study followed a systematic search and review of the literature to enter them into the selection process. The source guidelines' clinical suggestions were converted into clinical scenarios for clinical questions on the timing of decompressive surgery. After summarizing the scenarios, we prepared an initial list of recommendations based on the status of the Iranian patients and the health system. The ultimate conclusion was reached with the help of a national interdisciplinary expert panel comprising 20 experts throughout the country.A total of 408 records were identified. After title and abstract screening, 401 records were excluded, and the full texts of the remaining seven records were reviewed. Based on our screening process, only one guideline included recommendations on the topic of interest. All of the recommendations were accepted by the expert panel with slight changes due to resource availability in Iran. The final two recommendations were the consideration of early surgery (≤24 h) as a treatment option in adult patients with traumatic central cord syndrome and in adult patients with acute SCI regardless of the level of injury.Considering early surgery for adult patients with acute traumatic SCI regardless of the level of injury was the final recommendation for Iran. Although most of the recommendations are adoptable in developing countries, issues with infrastructure and availability of resources are the limitations.
Globalization of the fight against impunity and the Rome Statute of the International Criminal Court

Le 17 juillet 1998, la communauté internationale adopte le Statut de Rome prévoyant la création d’une Cour pénale internationale permanente pour juger les présumés responsables de crimes internationaux à une échelle universelle. L’objet de cette étude consiste, en effet, à examiner la capacité de la Cour pénale internationale à atteindre cet objectif.En réalité, la Cour constitue un progrès majeur vers une meilleure mise en œuvre du droit international humanitaire et un pas en avant manifeste dans la lutte contre l'impunité. Elle se distingue à bien d’égards des autres tribunaux pénaux internationaux et elle vient consolider et renforcer leurs acquis. Pour autant, l’ampleur des crimes et surtout le statut des sujets commettants sont autant d’éléments caractéristiques de son institution tardive mais également de la complexité de la mission qui lui est confiée. La photographie actuelle révèle que son activité est parsemée d’embûches, de défis politico-juridiques qui suscitent des critiques très vives par certains États, voire une délégitimation de son existence dans cette société actuelle fortement marquée par des violations graves des droits humains. Cela dit, ces critiques sont-elles fondées ? Peut-on imaginer notre société actuelle sans une Cour pénale internationale permanente, capable de de se saisir des situations de crimes internationaux ? Objectivement, même s’il convient de souligner que la CPI a montré ses insuffisances et ses failles, il est tout aussi fondamental de relever que la CPI est, aujourd’hui, une lueur d’espoirs pour toutes les victimes de crimes internationaux.
The Role of Lateral Extra-articular Tenodesis in Primary Anterior Cruciate Ligament Reconstruction: A Systematic Review With Meta-analysis and Best-Evidence Synthesis

Background:                     The role of lateral extra-articular tenodesis (LEAT) to augment primary anterior cruciate ligament reconstruction (ACLR) remains controversial.                                                           Purpose:                     To determine whether the addition of LEAT to primary ACLR provides greater control of rotational laxity and improves clinical outcomes compared with ACLR alone and to assess the impact of early versus delayed ACLR.                                                           Study Design:                     Systematic review; Level of evidence, 3.                                                           Methods:                     Two reviewers independently searched 7 databases for randomized and nonrandomized clinical studies comparing ACLR plus LEAT versus ACLR alone. Animal, cadaveric, and biomechanical studies; revision or repair procedures; and studies using synthetic ligaments and multiligamentous-injured knees were excluded. Risk of bias was assessed with a modified Downs and Black checklist. The primary outcome was postoperative pivot shift. These data were pooled by use of a fixed-effects meta-analysis model. The studies were divided into delayed (&gt;12 months) and early (≤12 months) reconstruction groups for meta-analysis. A best-evidence synthesis was performed on the remaining outcome measures.                                                           Results:                                            Of 387 titles identified, 11 articles were included (5 of high quality). Meta-analysis of postoperative pivot shift in 3 studies of delayed primary ACLR showed a statistically significant difference for the pivot-shift test in favor of ACLR with LEAT (odds ratio [OR], 0.44; 95% confidence interval [CI], 0.24-0.81; P = .008; I                       2                       = 0). Meta-analysis of 5 studies of early primary ACLR found no statistically significant difference with the addition of LEAT (OR, 0.60; 95% CI, 0.33-1.09; P = .10; I                       2                       = 33%). Insufficient evidence was available to determine whether the addition of LEAT had any effect on clinical, objective, subjective, and functional outcomes.                                                                                Conclusion:                     In primary ACLR, no evidence is available showing additional benefit of LEAT in reducing the postoperative pivot shift in early reconstructions (≤12 months); however, LEAT may have a role in delayed ACLR. Strong evidence exists that a combined ACLR and LEAT reduces lateral femoral translation, but there is insufficient evidence to identify any benefit for other clinical outcomes.
Nonequilibrium Thermodynamics of Chemical Reaction Networks: Wisdom from Stochastic Thermodynamics

We build a rigorous nonequilibrium thermodynamic description for open chemical reaction networks of elementary reactions. Their dynamics is described by deterministic rate equations satisfying mass action law. Our most general framework considers open networks driven by time-dependent chemostats. The energy and entropy balances are established and a nonequilibrium Gibbs free energy is introduced. The difference between this latter and its equilibrium form represents the minimal work done by the chemostats to bring the network in its nonequilibrium state. It is minimized in nondriven detailed-balanced networks (i.e. networks which relax to equilibrium states) and has an interesting information-theoretic interpretation. We further show that the entropy production of complex balanced networks (i.e. networks which relax to special kinds of nonequilibrium steady states) splits into two non-negative contributions. One charaterizing the dissipation of the nonequilibrium steady state and the other the transients due to relaxation and driving. Our theory lays the path to study time-dependent energy and information transduction in biochemical networks.
Changes in Specialists’ Perspectives on Cancer Genetic Testing, Prophylactic Surgery and Insurance Discrimination: Then and Now

Abstract                                        We surveyed cancer genetics specialists in 1998 to learn what they would do if at 50 % risk to carry a BRCA or Lynch syndrome mutation. We chose to repeat our study 14 years later, to examine how perspectives have changed with the extensive data now available. In July 2012 we surveyed the National Society of Genetic Counselors (NSGC) Cancer Special Interest Group via an internet based survey. We found statistically significant increases in the percentage of specialists who: would undergo BRCA testing (                     p                      = 0.0006), opt for prophylactic bilateral mastectomy (                     p                     =0.0001), opt for prophylactic removal of their uterus and ovaries for Lynch syndrome (                     p                     =0.0057 and                     P                      = 0.0090, respectively), and bill testing to insurance (                     p                     &gt;0.0001). There were also statistically significant decreases in the percentage of participants who would have their colon removed for Lynch syndrome (                     p                      = 0.0002) and use an alias when pursuing testing (                     p                      &gt; 0.0001). Over the past 14 years there has been a major change in perspective amongst cancer genetic specialists regarding genetic testing, prophylactic surgery and insurance discrimination.
Local Distribution Privacy in Federated Learning

Privacy is a well-researched area in the context of Federated Learning. Typically, ensuring privacy means that individual data used for local training cannot be reconstructed by other local learners or a central server. Thus, it is the individual data points that should be private, but not the entire distribution of locally available data. In many cases, this makes sense because each data point comes from a different individual while all data points originate from a common global distribution. In this position paper, we address a more challenging task where the privacy of each local data distribution must be preserved. This is relevant for use cases where there is a one-to-one mapping from local learners to users, such as when each local learner is part of a personalized assistant on a smartphone. We provide a definition of this problem case, describe the challenges that need to be addressed, and formulate a possible approach to solve the problem.