ethicalabs/Research-Intent-Collab huggingface dataset:
Using Topological Data Analysis to Process Time-series Data: A Persistent Homology Way

Abstract                Topological Data Analysis (TDA) is a novel new and strong-growing method to deal with various data in most areas. And Persistent Homology is one of the most pivotal tools in Topological Data Analysis to acquire topological properties of the data. This article is based on the main mathematics behind Topological and Topological Data Analysis. And it describes how to use the above theories and methods to do the analysis job for time-series data. Moreover, it discusses the further applications of TDA to other domains and the combination of machine learning with Topological Data Analysis. The article outlines the TDA model and principle behind the data set and provides insights into the function of TDA for time-series analysis as well as opportunities for future work.
The hitchhiker's guide to generic ecological-economic modelling of land-use-based biodiversity conservation policies

Biodiversity loss is a result of interacting ecological and economic factors, and it must be addressed through an analysis of biodiversity conservation policies. Ecological-economic modelling is a helpful approach to this analysis, but it is also challenging since modellers often have a specific disciplinary background and tend to misrepresent either the ecological or economic aspects. Here, we introduce some of the most important concepts from both disciplines, and since the two modelling cultures also differ between the two disciplines, we present an integrated, consistent guide through all the steps of generic ecological-economic modelling, such as formulation of the research question, development of the conceptual model, model parametrisation and analysis, and interpretation of model results. Although we focus on generic models aimed at a general understanding of causes and remedies for biodiversity loss, the concepts and guidance provided here may also help in the modelling of more specific conservation problems. This guide is aimed at the intersection of three disciplines: ecology, economics and mathematical modelling, and addresses readers who have some knowledge in at least one of these disciplines and want to learn about the others to build and analyse generic ecological-economic models. Compared to textbooks, the guide focuses on the practice of modelling rather than lengthy explanations of theoretical concepts. We attempt to demonstrate that generic ecological-economic modelling does not require magical powers and instead is a manageable exercise.
Ethical Problems of Conducting Research and Building Peace in Conflict Environment: Example of the Institute for Peace and Conflict Resolution in Nigeria

The study examines the incessant cases of ethical challenges in research and peacebuilding in the Nigeria’s conflict environment. Due to rampant corruption and lack of specific national ethical framework, and regulatory committee and resources that have affected societal values and culture of ethics and integrity, peace and conflict researchers and practitioners are prone to unethical conducts. Some are committed knowingly and unknowingly. This aspect of professional life has not been closely scrutinized, let alone proffers suggestions to. Perhaps, ethics frameworks and administrations are just beginning to be mainstreamed into development work in most part of the world. Therefore, drawing qualitative data from a wide range of personal, career and desk top sources from the Institute for Peace and Conflict Resolution, which is the government’s apex agency saddled with the responsibility of investigating causes and dynamics of conflict, and advising decision makers on best policy alternatives, build peace and engage in advocacy, the study identifies numerous ethical problems that include copy and paste, manipulations of data, unhealthy competition/rivalry among researchers and peacebuilding practitioners working in the conflict field. The research uncovers approaches the institute adopted to ameliorate the problems and promote ethical standards among its research and peacebuilding teams that included trainings and constant reminders of the need to protect the integrity of individuals in the team and the Institute as well as the need to project a good image for the country. The inability to re-think ethical regime and legal norms in the country could fuel violent conflict and terrorism, and militate against the goals of conflict management in the country that is seriously desirous of peace and security.
One Health and Veterinary Microbiology: Interactions between environment, animals, and humans in the control of emerging pathogens

Emerging and reemerging pathogens pose a growing threat to global health, requiring integrated approaches that address the complex relationships among humans, animals, and the environment. This study explores how veterinary microbiology and the One Health framework can contribute to the detection, monitoring, and control of emerging pathogens at the interface between humans, animals, and the environment. A comprehensive literature review was conducted to identify key microbial threats and evaluate diagnostic, epidemiological, and preventive strategies used across sectors. Special emphasis was placed on bacterial and fungal pathogens with zoonotic potential, antimicrobial resistance patterns, and environmental drivers such as climate change, land use modification, and wildlife contact. The findings highlight the importance of early detection through molecular diagnostics, improved bio surveillance networks, and interdisciplinary collaboration among veterinary, medical, and environmental health professionals. Integrating veterinary microbiology into One Health strategies strengthens outbreak preparedness and response capacities, while also supporting more effective disease control and prevention measures. This work underscores the need for coordinated actions at local, national, and global levels to reduce health risks and protect both human and animal populations.
Merging Techniques for Combinatorial Optimization: Spectral Graph Theory and Semidefinite Programming.

In this thesis, we study three problems related to expanders, whose analysis involves understanding the intimate connection between expanders, spectra and semidefinite programming. Our first result is related to Khot's Unique Games conjecture (UGC), whose validity is one of the most central open problems in computational complexity theory. We show that UGC is false on expander graphs. This result, in particular, rules out a natural way of proving hardness of approximation for SPARSEST CUT. Our second result is in the area of graph sparsification. We say that a graph H is a sparsifier for a graph G if the respective graph Laplacians of the two graphs satisfy xTLHx &le xTLGx, for all vectors x. Given a union of two graphs G+W, we show how to choose a sparse subgraph W' of W so that G+W' is a good sparsifier for G+W. We apply the result to optimizing the algebraic connectivity of a graph by adding very few edges. We also show how to use this result in order to create optimal ultrasparsifiers for every graph, which can be used as good graph theoretic preconditioners for symmetric, positive semidefinite, diagonally dominant linear systems. Lastly, we study the integrality gap of the well known Sparsest Cut semidefinite program. We present a simple construction and analysis of an ­O(log logN) integrality gap for Sparsest Cut while our gap instance, vector solution, and analysis are somewhat simpler and more intuitive than those which appear in the literature.Our techniques use tools both from the area of semidefinite programming and spectral graph theory. This is not surprising since, when delving into the beautiful theory underlying spectra and SDPs, one finds that they are deeply connected in more ways than one.Semidefinite programs are nothing but linear programs with variables representing entries of a matrix, together with eigenvalue bounds for that matrix and could, therefore capture the spectral expansion of a graph. Similarly, most of eigenvalue optimization problems canbe cast as SDPs, which leads to ...
Error correction and symmetrization in quantum computers

18 pages LaTeX + 1 figure PostScript. Proceedings of PhysComp'96 workshop, Boston 21-24 November 1996, to appear in Physica D (1997)
A joint function warm-up and request routing scheme for performing confident serverless computing

Serverless computing has become increasingly popular recently due to its cost efficiency and flexibility. However, running serverless computing functions in the cloud can incur high end-to-end service latency and operational costs. Running them on edge servers may significantly reduce service latency but is limited by computing power and memory availability. Given the limitations of cloud and edge environments for performing serverless computing, this paper proposes a joint function warm-up and request routing scheme to perform serverless computing functions on edge and cloud collaboratively. The key idea of the new scheme is to maximize the hit ratio of serverless computing requests, thereby reducing the cold-start latency that dominates the overall serving latency. This scheme explicitly considers allocating server memory and operation budget for executing concurrent requests during the scheduling. The proposed scheme has been evaluated through extensive simulations. Its effectiveness has been proved by comparison with the upper-bound results.
Dynamical interstellar medium with Gaia and ground-based massive spectroscopic stellar surveys

The ongoing Gaia mission of ESA will provide accurate spatial and kinematical information for a large fraction of stars in the Galaxy. Interstellar extinction and line absorption studies toward a large number of stars at different distances and directions can give a 3-dimensional distribution map of interstellar absorbers, and thus reach a similar spatial perfection. Under certain morphologies (e.g. geometrically thin absorption curtains) one can infer a complete velocity vector from its radial velocity component and so obtain a dynamical information comparable to stars. But observations of a large number of stars at different distances are needed to determine the location of the absorption pockets. Therefore, techniques to measure interstellar absorptions towards (abundant) cool stars are needed.   A complex mix of colliding absorption clouds is found in the Galactic plane. Thus, one would wish to start with deep observations to detect the weak, but simpler interstellar absorptions at high Galactic latitudes. Finally, interstellar atomic line absorption studies toward cool stars in the optical are largely limited to Sodium and Potassium doublets, not covered by many surveys, including Gaia. Diffuse interstellar bands can give the same type of information as interstellar atomic absorption lines. A combination of both may also point to differences in dynamics of different components of the interstellar medium. In particular, the Gaia DIB at 862 nm can be used to build absorption maps, as already demonstrated by RAVE. Additionally, several ground-based surveys (e.g APOGEE, Gaia-ESO and Galah) are upgrading this approach. The use of this new information can change our understanding in many areas (e.g. determination of membership of stars in clusters, studies of a few Myr old supernova remnants and investigations of Galactic fountains).
Acceleration of Moving Object Detection in Bio-Inspired Computer Vision

Computer vision is a great interest field offering relevant information in a wide variety of areas. Different video processing techniques, for instance, allow us to detect moving objects from image sequences of fixed surveillance cameras. Lateral Interaction in Accumulative Computation is a classical bio-inspired method that is usually applied for detecting moving objects in video processing. This method achieves high precision but also requires a high processing time. This paper introduces a parallel code capable of keeping a high performance in terms of accuracy and runtime for the method. For some of the image sequences tested, a speed-up of \(67\times \) over the sequential counterpart is achieved.
HCFContext: Smartphone Context Inference via Sequential History-based Collaborative Filtering

Mobile context determination is an important step for many context aware services such as location-based services, enterprise policy enforcement, building or room occupancy detection for power or HVAC operation, etc. Especially in enterprise scenarios where policies (e.g., attending a confidential meeting only when the user is in "Location X") are defined based on mobile context, it is paramount to verify the accuracy of the mobile context. To this end, two stochastic models based on the theory of Hidden Markov Models (HMMs) to obtain mobile context are proposed-personalized model (HPContext) and collaborative filtering model (HCFContext). The former predicts the current context using sequential history of the user's past context observations, the latter enhances HPContext with collaborative filtering features, which enables it to predict the current context of the primary user based on the context observations of users related to the primary user, e.g., same team colleagues in company, gym friends, family members, etc. Each of the proposed models can also be used to enhance or complement the context obtained from sensors. Furthermore, since privacy is a concern in collaborative filtering, a privacy-preserving method is proposed to derive HCFContext model parameters based on the concepts of homomorphic encryption. Finally, these models are thoroughly validated on a real-life dataset.
A Measurement of the Angular Power Spectrum of the Anisotropy in the Cosmic Microwave Background

We report on a measurement of the angular power spectrum of the anisotropy in the Cosmic Microwave Background. The anisotropy is measured in 23 different multipole bands from l=54 (~3 deg) to l=404 (~0.45 deg) and in 6 frequency bands from 26 GHz to 46 GHz over three observing seasons. The measurements are consistent from year to year. The frequency spectral index of the fluctuations (measured at low l) is consistent with that of the CMB and inconsistent with either dust or Galactic free-free emission. Furthermore, the observations of the MSAM1-92 experiment (Cheng et al. 1994) are repeated and confirmed. The angular spectrum shows a distinct rise from dT_l = \sqrt{l(2l+1)/4pi} = 49(+8,-5) \uK at l=87 to dT_l=85(+10,-8) uK at l = 237. These values do not include an overall +/-14\% (1sigma) calibration uncertainty. The analysis and possible systematic errors are discussed.
Digital Phenotyping for Mental Health:Reviewing the Challenges of Using Data to Monitor and Predict Mental Health Problems

PURPOSE OF REVIEW: We review recent developments within digital phenotyping for mental health, a field dedicated to using digital data for diagnosing, predicting, and monitoring mental health problems. We especially focus on recent critiques and challenges to digital phenotyping from within the social sciences.RECENT FINDINGS: Three significant strands of criticism against digital phenotyping for mental health have been developed within the social sciences. This literature problematizes the idea that digital data can be objective, that it can be unbiased, and argues that it has multiple ethical and practical challenges. Digital phenotyping for mental health is a rapidly growing and developing field, but with considerable challenges that are not easily solvable. This includes when, and if, data from digital phenotyping is actionable in practice; the involvement of user and patient perspectives in digital phenotyping research; the possibility of biased data; and challenges to the idea that digital phenotyping can be more objective than other forms of psychiatric assessment.
Twin Transition: Digital Transformation Pathways for Sustainable Innovation

This paper examines how organizations and regions integrate digital transformation with environmental sustainability (“twin transition”). Based on 43 semi-structured expert interviews across 27 countries, we identify five empirically grounded insights. First, adoption is propelled by competitive pressure, external shocks, and rising regulatory and stakeholder demands. Second, success depends on internal capabilities—clear leadership vision and workforce skills—together with supportive regional innovation ecosystems. Third, deliberate technological synergies—especially digital twins for lifecycle optimization, Artificial Intelligence (AI)/analytics and Internet of Things (IoT) for monitoring, and blockchain for traceability—enable measurable gains in resource efficiency and environmental performance. Fourth, integration strengthens eco-innovation capacity, resilience to disruption, competitive positioning, and regional innovation dynamics. Fifth, persistent barriers remain; organizational silos, key performance indicators (KPIs) misalignment, rebound effects from digital infrastructures, and uneven regional capabilities. By linking enabling conditions, integration mechanisms, and barriers, the study advances theory and offers actionable guidance for managers and policymakers on realizing the twin transition, using descriptive counts to indicate salience within a purposive expert sample rather than to draw statistical inferences.
From Revisions to Insights: Converting Radiology Report Revisions into Actionable Educational Feedback Using Generative AI Models

Abstract           Expert feedback on trainees’ preliminary reports is crucial for radiologic training, but real-time feedback can be challenging due to non-contemporaneous, remote reading and increasing imaging volumes. Trainee report revisions contain valuable educational feedback, but synthesizing data from raw revisions is challenging. Generative AI models can potentially analyze these revisions and provide structured, actionable feedback. This study used the OpenAI GPT-4 Turbo API to analyze paired synthesized and open-source analogs of preliminary and finalized reports, identify discrepancies, categorize their severity and type, and suggest review topics. Expert radiologists reviewed the output by grading discrepancies, evaluating the severity and category accuracy, and suggested review topic relevance. The reproducibility of discrepancy detection and maximal discrepancy severity was also examined. The model exhibited high sensitivity, detecting significantly more discrepancies than radiologists (W = 19.0, p &lt; 0.001) with a strong positive correlation (r = 0.778, p &lt; 0.001). Interrater reliability for severity and type were fair (Fleiss’ kappa = 0.346 and 0.340, respectively; weighted kappa = 0.622 for severity). The LLM achieved a weighted F1 score of 0.66 for severity and 0.64 for type. Generated teaching points were considered relevant in ~ 85% of cases, and relevance correlated with the maximal discrepancy severity (Spearman ρ = 0.76, p &lt; 0.001). The reproducibility was moderate to good (ICC (2,1) = 0.690) for the number of discrepancies and substantial for maximal discrepancy severity (Fleiss’ kappa = 0.718; weighted kappa = 0.94). Generative AI models can effectively identify discrepancies in report revisions and generate relevant educational feedback, offering promise for enhancing radiology training.
Changes to the Employers' Use of Genetic Information and Non-discrimination for Health Insurance in the USA: Implications for Australians

In the USA, a bill has been introduced to the senate that may jeopardize an individual's rights to privacy and non-discrimination. This piece examines the proposed Preserving Employee Wellness Programs Act (PEWPA), and implications this will have on the use of genetic information. The Act allows for employers to apply financial penalties for health insurance based on genetic information, which raises concerns as the capacity to interpret genetic results is limited by knowledge of the significance of both benign and pathogenic variants. In Australia, genetic information can only be used to determine life insurance, not to stratify health insurance, and any precedent set internationally should raise concerns of the potential for change on the horizon.
RETRACTED: Li, J. Fault-Event Trees Based Probabilistic Safety Analysis of a Boiling Water Nuclear Reactor’s Core Meltdown and Minor Damage Frequencies. Safety 2020, 6, 28

The author would like to retract the article, published on 17 June 2020, cited above [...]
Effects and cost-effectiveness of postoperative oral analgesics for additional postoperative pain relief in children and adolescents undergoing dental treatment: Health technology assessment including a systematic review

There is an uncertainty regarding how to optimally prevent and/or reduce pain after dental treatment on children and adolescents.To conduct a systematic review (SR) and health technology assessment (HTA) of oral analgesics administered after dental treatment to prevent postoperative pain in children and adolescents aged 3-19 years.A PICO-protocol was constructed and registered in PROSPERO (CRD42017075589). Searches were conducted in PubMed, Cochrane, Scopus, Cinahl, and EMBASE, November 2018. The researchers (reading in pairs) assessed identified studies independently, according to the defined inclusion and exclusion criteria, following the PRISMA-statement.3,963 scientific papers were identified, whereof 216 read in full text. None met the inclusion criteria, leading to an empty SR. Ethical issues were identified related to the recognized knowledge gap in terms of challenges to conduct studies that are well-designed from methodological as well as ethical perspectives.There is no scientific support for the use or rejection of oral analgesics administered after dental treatment in order to prevent or reduce postoperative pain in children and adolescents. Thus, no guidelines can be formulated on this issue based solely on scientific evidence. Well-designed studies on how to prevent pain from developing after dental treatment in children and adolescents is urgently needed.
Brain activation in parietal area during manipulation with a surgical robot simulator

we present an evaluation method to qualify the embodiment caused by the physical difference between master-slave surgical robots by measuring the activation of the intraparietal sulcus in the user's brain activity during surgical robot manipulation. We show the change of embodiment based on the change of the optical axis-to-target view angle in the surgical simulator to change the manipulator's appearance in the monitor in terms of hand-eye coordination. The objective is to explore the change of brain activation according to the change of the optical axis-to-target view angle.In the experiments, we used a functional near-infrared spectroscopic topography (f-NIRS) brain imaging device to measure the brain activity of the seven subjects while they moved the hand controller to insert a curved needle into a target using the manipulator in a surgical simulator. The experiment was carried out several times with a variety of optical axis-to-target view angles.Some participants showed a significant peak (P value = 0.037, F-number = 2.841) when the optical axis-to-target view angle was 75°.The positional relationship between the manipulators and endoscope at 75° would be the closest to the human physical relationship between the hands and eyes.