ethicalabs/Research-Intent-Collab huggingface dataset:
Modeling Impact of Climate Change in Hydropower Projects’ Feasibility Valuation

In this paper a case study is presented to propose an alternative mechanism to include the impact of climate change into the hydropower projects’ feasibility valuation. We start from independent engineer historical energy generation simulations, therefore applying mixing unconditional disturbance and extreme value theory, a new path that satisfy a return level specification is created. New path is used to analyze the effect of extreme events on the internal rate of return of the project. This mechanism could be used also to execute a simple sensitivity test that it’s done with an educated guess.
Visualize the universe: Interactive exploration of cosmological dark matter simulation data

In this paper we propose a unified visualization tool for cosmological data resulting from dark matter simulations. Our system comprises both established and novel visualization approaches for the dark matter tracer particles and halo structures to allow interactive exploration of the data in 3D and 2D as well as tracking the evolution of the data over time using multiple views. Due to our scalable volume rendering approach, properties of the particle data such as the distribution of dark matter can be visualized at interactive frame rates even for large-scale data after a one-time pre-processing conversion step.
Approximation of Intractable Likelihood Functions in Systems Biology via Normalizing Flows

Systems biology relies on mathematical models that often involve complex and intractable likelihood functions, posing challenges for efficient inference and model selection. Generative models, such as normalizing flows, have shown remarkable ability in approximating complex distributions in various domains. However, their application in systems biology for approximating intractable likelihood functions remains unexplored. Here, we elucidate a framework for leveraging normalizing flows to approximate complex likelihood functions inherent to systems biology models. By using normalizing flows in the Simulation-based inference setting, we demonstrate a method that not only approximates a likelihood function but also allows for model inference in the model selection setting. We showcase the effectiveness of this approach on real-world systems biology problems, providing practical guidance for implementation and highlighting its advantages over traditional computational methods.
Bridging the Phylogenetic Gap: The Small-Spotted Catshark as a Key Model Organism in Evolutionary Developmental Biology

The evolution and diversification of vertebrates is largely associated with changes in their developmental programs. In order to reconstruct the evolution of developmental programs, species from different phylogenetic lineages are typically compared. Despite the expansion of available species in the recent years, current research remains biased towards bony vertebrates (Osteichthyes), which includes the classical model organisms: mouse, chicken, clawed frogs, and zebrafish. As a consequence, a key vertebrate lineage remains comparatively understudied: Chondrichthyes (cartilaginous fishes). In this thesis, I re-introduce the small-spotted catshark (Scyliorhinus canicula) as a powerful chondrichthyan model organism in evolutionary developmental biology (evo-devo) with the aim to bridge the gap between the emerging field of lamprey research and the vast information gathered from osteichthyan model organisms. I generate a high-resolution atlas of the developing small-spotted catshark combining combining synchrotron radiation micro-computed tomography (SRµCT) with gene expression mapping. Subsequently, I characterize the developmental dynamics of CNCCs as well as facial morphogenesis. Collectively, I identify heterochronic and heterotopic changes in developmental programs, as well as providing novel insights into chondrichthyan development. Overall, this work expands the evolutionary developmental framework by integrating morphological and molecular data from an underrepresented vertebrate lineage. It demonstrates the feasibility of applying cutting-edge methodologies to non-model organisms, and establishes a foundation for future comparative studies. The resources generated here will be made publicly available, offering valuable tools for the scientific community and aiding in the broader inclusion of Chondrichthyes into evo-devo research.
Poland’s Rule of Law Breakdown Continued: Judge Żurek’s Battle for Judicial Independence Within the European Human Rights Framework

Abstract Judicial independence and rule of law in Poland have been increasingly under challenge before national and European courts. Departing from a case study of Judge Żurek, an emblematic figure of the Polish judicial community prosecuted for criticizing the post-2015 judicial reforms, this article assesses how the European Human Rights framework can play out in a particular case of a judge defending the rule of law in his country. After having outlined the circumstances of his prosecution, it follows his journey to Luxembourg and Strasbourg. Namely, it lays out the legal issues before the Courts and examines the standards they establish, commenting on how they translate into prospects of redress. It finds that, while both the cjeu and the ECtHR establish standards on court transfers, judicial nominations, premature termination of office or the link to freedom of expression, the level of judicial independence required for their successful implementation creates a paradox.
Pilot study on effectiveness of simulation for surgical robot design using manipulability

Medical technology has advanced with the introduction of robot technology, which facilitates some traditional medical treatments that previously were very difficult. However, at present, surgical robots are used in limited medical domains because these robots are designed using only data obtained from adult patients and are not suitable for targets having different properties, such as children. Therefore, surgical robots are required to perform specific functions for each clinical case. In addition, the robots must exhibit sufficiently high movability and operability for each case. In the present study, we focused on evaluation of the mechanism and configuration of a surgical robot by a simulation based on movability and operability during an operation. We previously proposed the development of a simulator system that reproduces the conditions of a robot and a target in a virtual patient body to evaluate the operability of the surgeon during an operation. In the present paper, we describe a simple experiment to verify the condition of the surgical assisting robot during an operation. In this experiment, the operation imitating suturing motion was carried out in a virtual workspace, and the surgical robot was evaluated based on manipulability as an indicator of movability. As the result, it was confirmed that the robot was controlled with low manipulability of the left side manipulator during the suturing. This simulation system can verify the less movable condition of a robot before developing an actual robot. Our results show the effectiveness of this proposed simulation system.
Sorting in Space: Multidimensional, spatial, and metric data structures for applications in spatial databases, geographic information systems (GIS), and location-based services

Techniques for representing multidimensional, spatial, and metric data for applications in spatial databases, geographic information systems (GIS), and location-based services are reviewed. This includes both geometric and textual representations of spatial data.
Metagenomic analysis of the lung tuberculomas microbiome

Introduction.             Globally, an estimated 10.0 million (range, 9.0–11.1 million) people fell ill with tuberculosis (TB) in 2018, a number that has been relatively stable in recent years [1]. Despite the obvious differences in the virulence and transmissibility of different genotypes [2], the pathogenesis of tuberculosis, especially in the later stages, is still poorly understood [3]. At the same time, some researchers suggest that the ability of Mycobacterium tuberculosis to form biofilms in vivo [3] is an important aspect of pathogenesis TB that should be used in the development of new generation vaccines [4]. Previously, we suggested that in the long treatment of TB, a specific lung microbiota can develop in the caseous contents of tuberculosis foci, forming a polymicrobial biofilm, resistant to anti-tuberculosis therapy and contributing to the survival of M. tuberculosis [5]. Here, we present results of the metagenomic analysis of 14 tuberculomas and discuss the results obtained.                                   Methods.             The study recruited 13 patients undergoing planned surgical treatment at the Irkutsk Regional TB Hospital, Russia. DNA was isolated from caseous contents of 14 tuberculomas obtained during surgery. Two samples were obtained from one patient at two time points separated by six months.                                   Results.             Among 5167 bacterial reads, a total of 105 families were identified. Of them, 68 taxa belonged to Gram-negative bacteria, and 35 to Gram-positive. At the same time, the number of reads of Gram-negative and Gram-positive taxa was very similar - 2430 and 2746, respectively. This was probably due to the presence of 1801 reads from the family Mycobacteriaceae (M. tuberculosis). The microbial content of the tuberculomas was estimated as 104 -108 bacterial genomes per 1 gram of sample. The vast majority of reads (over 95%) were attributed to the human DNA. We have subdivided the samples into two types of bacterial communities: (i) paucibacillary bacterial community with a predominance of TB (63%-96%) and (ii) low-bacterial community with a predominance of non-mycobacterial taxa (13%-38%). Staphylococcaceae, Pseudomonadaceae, Eggerthellaceae, Pasteurellaceae, and Acetobacteraceae prevailed among non-mycobacterial communities.                                   Conclusions.             It can be unambiguously concluded that the microbiota of about half of the tuberculomas did not have a dominant taxon or it differed from M. tuberculosis.                                   Acknowledgments.             This work was supported by Russian Foundation for Basic Research (Grant No. 19-515-55009).
ChemInform Abstract: Transition‐Metal‐Doped M‐Li<sub>8</sub>ZrO<sub>6</sub> (M: Mn, Fe, Co, Ni, Cu, Ce) as High‐Specific‐Capacity Li‐Ion Battery Cathode Materials: Synthesis, Electrochemistry, and Quantum Mechanical Characterization.

AbstractTransition‐metal‐doped Li8ZrO6/C composites are prepared by heating mixtures of zirconyl nitrate, the dopant metal nitrate, and Super P carbon from room temperature to 400 °C followed by cooling back to room temperature.
Distributed Analytics and Edge Intelligence

Biomedical research and clinical practice are entering a data-driven era. One of the major applications of biomedical big data research is to utilize inexpensive and unobtrusive mobile biomedical sensors and cloud computing for pervasive health monitoring. However, real-world user experiences with mobile cloud-based health monitoring were poor, due to the factors such as excessive networking latency and longer response time. On the other hand, fog computing, a newly proposed computing paradigm, utilizes a collaborative multitude of end-user clients or near-user edge devices to conduct a substantial amount of computing, storage, communication, and etc. This new computing paradigm, if successfully applied for pervasive health monitoring, has great potential to accelerate the discovery of early predictors and novel biomarkers to support smart care decision making in a connected health scenarios. In this paper, we employ a real-world pervasive health monitoring application (pervasive fall detection for stroke mitigation) to demonstrate the effectiveness and efficacy of fog computing paradigm in health monitoring. Fall is a major source of morbidity and mortality among stroke patients. Hence, detecting falls automatically and in a timely manner becomes crucial for stroke mitigation in daily life. In this paper, we set to (1) investigate and develop new fall detection algorithms and (2) design and employ a real-time fall detection system employing fog computing paradigm (e.g., distributed analytics and edge intelligence), which split the detection task between the edge devices (e.g., smartphones attached to the user) and the server (e.g., servers in the cloud). Experimental results show that distributed analytics and edge intelligence, supported by fog computing paradigm, are very promising solutions for pervasive health monitoring.
Humanitarian Intervention and Responsibility to Protect

The book examine interventions in Sri Lanka, Iraq 1991, Somalia, Kosovo, East Timor, Iraq 2003, Libya and Syria. Despite strategic and ideological shifts, the influence of values remained consistent. India, applying non-violence to the level of nation-states and peoples rather than individuals, focuses on interstate violence rather than on violence at the ‘human security’ level. Delhi’s level of support for an intervention equates to the scale of the humanitarian suffering, minus the level of interstate violence required to resolve it. India’s engagement with R2P was governed by pre-existing values. Delhi’s pluralistic and tolerant worldview entailed acceptance of various regime types amongst states. Democratic India thereby stood in opposition to fellow democracies in the West over intervention. Pluralism led to preferences for UN/legal authorization of interventions, sovereignty and regional action.
The moral imperative of designating patient safety and quality care as a national nursing research priority

Since the early 1990s, research studies conducted respectively in the USA, UK and Australia have found that between 4 and 16.6 per cent of patients suffer from some kind of harm (including permanent disability and death) as a result of human errors and adverse events while in hospital. It has been further estimated that approximately 50 per cent of these human errors/adverse events resulting in harm could have been prevented. In response to the significant financial, social, and political implications of these figures, a range of processes have been put in place in an attempt to improve patient safety and quality care in Australia. Nonetheless, it is evident that more can be done to improve the status quo. One process that warrants consideration is that of peak health professional groups and organisations providing active leadership in the promotion of patient safety, such as by making a visible and recognisable commitment to patient safety as a strategic research priority area. In this paper it is contended that, given the moral importance of patient safety and quality care in nursing and related health care domains, the inseparable link between nursing practice and patient safety, and the central role that research has to play in driving safety improvements in these domains, it is morally imperative that the nursing profession gives sustained and focussed public attention to patient safety and quality care as a national research priority.
sj-pdf-1-pmj-10.1177_02692163211019321 – Supplemental material for Improved quality of care and reduced healthcare costs at the end-of-life among older people with dementia who received palliative home care: A nationwide propensity score-matched decedent cohort study

Supplemental material, sj-pdf-1-pmj-10.1177_02692163211019321 for Improved quality of care and reduced healthcare costs at the end-of-life among older people with dementia who received palliative home care: A nationwide propensity score-matched decedent cohort study by Rose Miranda, Tinne Smets, Robrecht De Schreye, Kristof Faes, Nele Van Den Noortgate, Joachim Cohen and Lieve Van den Block in Palliative Medicine
Sexual and reproductive health rights of Colombian IDPs

Meeting the sexual and reproductive needs ofdisplaced Colombians must be part of a process ofrestoring their lost rights of citizenship.
Probing the physics of reionization using kinematic Sunyaev–Zeldovich power spectrum from current and upcoming cosmic microwave background surveys

ABSTRACT                The patchiness in the reionization process alters the statistics of cosmic microwave background (CMB), with the kinematic Sunyaev–Zeldovich (kSZ) effect in the CMB temperature power spectrum being a notable consequence. In this work, we aim to explore the potential of future kSZ power spectrum measurements in inferring the details of the reionization process. In this pursuit, we capitalize on the recent developments in foreground mitigation techniques using the Cross-Internal Linear Combination (Cross-ILC) technique, which enables robust detection of the kSZ power spectrum with signal-to-noise ratio roughly 20σ–30σ in this decade by South pole Telescope (SPT-3G) and Simons Observatory (SO); and ≥80σ by CMB-S4 – substantially improving on the recent evidence for kSZ binned at ℓ = 3000 using SPT-SZ + SPTpol surveys. We use a fiducial kSZ power spectrum along with realistic error bars expected from the above technique for SPT-3G, SO, and CMB-S4 to constrain the parameter space for a physical model of reionization. We find that with the improved error bars it will be possible to place stringent constraints on reionization using solely the Cross-ILC recovered SPT-3G kSZ without imposing any prior on τ in the Bayesian inference. Notably, high-fidelity kSZ measurements from CMB-S4 coupled with τ measurements through LiteBIRD will enable unprecedented constraint on the midpoint of reionization with an error bar of ∼0.25 and the duration of reionization with an error bar at ∼0.21 exclusively using CMB data. This study highlights the need to capture kSZ power spectrum on a broad range of multipoles to gain insights into the inhomogeneous reionization era.
Building National and Regional Accountability for Conflict Related Sexual Violence: From Prosecutions in the Former Yugoslavia to the African Court of Justice and Human and Peoples’ Rights

The jurisdiction of the African Court of Justice and Human and Peoples’ Rights (acjhpr) will include international crimes of conflict-related sexual violence (crsv). This article explores the challenges the Court is likely to face in building regional and national accountability for crsv, by considering the lessons that might be learnt from the experiences of the former Yugoslavia in prosecuting these crimes. The article focuses on the two key challenges of developing ‘best practice’ within regional and national courts, and of linking these prosecutions to peace processes and post-conflict reconstruction. To address these challenges, the article argues for a ‘gender justice framework’ of guiding principles to ensure effective and equitable crsv prosecutions.
The One Health concept – the health of humans is intimately linked with the health of animals and a sustainable environment

Content List ‐ This is an article from the symposium: “Bioinspirational medicine”.
P02.35. Methodology in integrative medicine research: challenges and solutions from a randomized clinical control trial using adapted yoga

Purpose  This randomized controlled clinical study evaluated the efficacy of adapted yoga (vs. usual care) to reduce psychosocial risks, which have been clinically shown to impact morbidity and mortality in implantable cardioverter defibrillator (ICD) recipients. The ICD collects and records real-time cardiac data, which were used in the study.  Methods  Forty-six patients participated from a hospital in Connecticut. All participants were administered validated measures on psychosocial risk factors at weeks one and eight of the eight-week intervention. Patients in the intervention group participated in a weekly adapted yoga class for eighty minutes for eight weeks with assigned home practices. Clinical measures, including patients’ current and past medical health status and device usage, were collected three months prior to the study, during the study, and at a six-month follow-up.  Results  Data revealed that the yoga group’s overall shock anxiety decreased while the control group’s increased, t(4.43, 36), p<0.0001 (total). The yoga group had less shock anxiety, t(2.86,36) p=0.007 (mean consequence), greater overall self-compassion, t(-2.84,37), p=0.007 (total), and greater mindfulness (equanimity) regarding emotions, t(-2.10,37) p=0.04 (mindfulness), than the control group. Exploratory analyses utilizing a linear model (R2=.98) of the observed anti-tachycardia pacing (ATP) events revealed that the expected number of ATP events in the intervention group was significantly lower than the control group. Additionally, the expected number of ATP events increased more rapidly as a function of the initial ATP events for the control group than for the intervention group.  Conclusion  Our study demonstrated psychological benefits from a program of adapted yoga compared to usual care for ICD recipients. Marked improvements were reported in total shock anxiety, self-compassion, sense of equanimity, and decreased likelihood of ATPs. The data supports the continuation of research in mind-body interventions to better understand the role of complementary medicine to address ICD-specific psychosocial stress and its potential contributory role in cardiac outcomes.
UCF-MultiOrgan-Path:A Benchmark Dataset of Histopathologic Images for Deep Learning-Based Organ Classification

ABSTRACT                 A pathologist typically diagnoses tissue samples by examining glass slides under a light microscope. The entire tissue specimen can be stored digitally as a Whole Slide Image (WSI) for further analysis. However, managing and diagnosing large numbers of images manually is time-consuming and requires specialized expertise. Consequently, computer-aided diagnosis of these pathology images is an active research area, with deep learning showing promise in disease classification and cancer cell segmentation. Robust deep learning models need many annotated images, but public datasets are limited, often constrained to specific organs, cancer types, or binary classifications, which limits generalizability. To address this, we introduce the UCF multi-organ histopathologic (UCF-MultiOrgan-Path) dataset, containing 977 WSIs from cadaver tissues across 15 organ classes, including lung, kidney, liver, and pancreas. This dataset includes ∼2.38 million patches of 512×512 pixels. For technical validation, we provide patch-based and slide-based approaches for patch- and slide-level classification. Our dataset, containing millions of patches, can serve as a benchmark for training and validating deep learning models in multi-organ classification.