ethicalabs/Research-Intent-Collab huggingface dataset:
A Checklist for Ascertaining Study Cohorts in Oncology Health Services Research Using Secondary Data: Report of the ISPOR Oncology Good Outcomes Research Practices Working Group

The ISPOR Oncology Special Interest Group formed a working group at the end of 2010 to develop standards for conducting oncology health services research using secondary data. The first mission of the group was to develop a checklist focused on issues specific to selection of a sample of oncology patients using a secondary data source.A systematic review of the published literature from 2006 to 2010 was conducted to characterize the use of secondary data sources in oncology and inform the leadership of the working group prior to the construction of the checklist. A draft checklist was subsequently presented to the ISPOR membership in 2011 with subsequent feedback from the larger Oncology Special Interest Group also incorporated into the final checklist.The checklist includes six elements: identification of the cancer to be studied, selection of an appropriate data source, evaluation of the applicability of published algorithms, development of custom algorithms (if needed), validation of the custom algorithm, and reporting and discussions of the ascertainment criteria. The checklist was intended to be applicable to various types of secondary data sources, including cancer registries, claims databases, electronic medical records, and others.This checklist makes two important contributions to oncology health services research. First, it can assist decision makers and reviewers in evaluating the quality of studies using secondary data. Second, it highlights methodological issues to be considered when researchers are constructing a study cohort from a secondary data source.
Public Money in the Digital Era : An Institutionalist Analysis of Central Bank Digital Currencies

This thesis takes an institutionalist approach to the changes that Central Bank Digital Currencies (CBDC) will bring to monetary systems. It is structured around 3 thematic chapters, complemented by a literature review and a genealogical chapter on the concept of CBDCs. The literature review (Chapter 1) re-apprehends the results of the research field through the prism of Michel Aglietta and André Orléan's theory of monetary ambivalence. Our aim here is to determine the way in which the new central element of CBDCs will impact the structure of the banking system. And to analyze how the interactions between central banks and commercial banks will rearrange themselves, leading to a new form of monetary hierarchy. Chapter 2 proposes a genealogy of the CBDC concept. To do this, we recontextualize the current debate within the long-running discussion about the digitization of the monetary base. In particular, we look back at the various discussions held in the 1990s and 2000s on the subject of issuing public e-money, all of which (with one exception) failed to materialize.Our institutionalist framework enables us to understand this monetary innovation, beyond its quantitative dimension, through its technical characteristics and political implications, which can only be analyzed qualitatively. Our analysis focuses particularly on how CBDCs could be appropriated by state actors. In this sense, we are interested in how different policy frameworks and modes of economic governance might benefit from this monetary innovation. Chapter 3 focuses on the digital euro project, and more specifically on the European Central Bank's (ECB) communication about it. We analyze how the ECB interprets its mandate to legitimize its approach to the digital euro. This analysis also provides an opportunity to compare the ECB's approach with other European CBDC proposals from civil society. Chapter 4 examines the Chinese CBDC project. This new currency is presented as a digital infrastructure, one of whose main objectives seems to be to collect and process the Big Data that its functionning will generate. Chapter 5 looks at the multi-CBDC platforms on which national digital currencies will circulate, designed to facilitate the settlement of international transfers. These infrastructures will create network effects that are different from those achieved by the current correspondent banking system and will necessarily have an impact on the functioning of the International Monetary System (IMS).Therefore, our thesis presents a relatively varied panorama of the different developments that CBDCs are likely to bring about, both technically and in terms of economic governance, and on both a domestic and international scale.
Aquaculture wastewater management in Nigeria's fisheries industry for sustainable aquaculture practices

La contaminación ambiental derivada de las aguas residuales de la acuicultura es cada vez más importante en Nigeria a medida que la industria de la acuicultura continúa creciendo para satisfacer las necesidades de proteína animal del país y aliviar su crisis de inseguridad alimentaria. Este aumento en el número de piscifactorías en el país, junto con un aumento concomitante de las aguas residuales de la acuicultura, tiene un costo. Los componentes vitales de las aguas residuales de la acuicultura son restos de alimento no consumido, materiales sedimentarios y desechos metabólicos de las especies de peces cultivadas. Estos constituyentes varían en fisicoquímica, volumen, composición y carga microbiana dependiendo del tipo de sistema de cultivo practicado. Algunos de los efectos negativos de la liberación de aguas residuales de la acuicultura en los ambientes acuáticos son la eutrofización del agua receptora, la intoxicación alimentaria, la contaminación del agua dulce, la bioacumulación de metales por la biota acuática, el aumento de la prevalencia de enfermedades entre los habitantes de los ecosistemas contaminados y, en situaciones extremas, la pérdida de recursos acuáticos comercialmente valiosos y viables. Se han desarrollado varias tecnologías para tratar las aguas residuales de la acuicultura e incluyen: humedales construidos, sistemas de acuicultura recirculatoria, fitorremediación, nanotecnología, así como procesos físicos y biológicos. Estos métodos varían en eficacia, rentabilidad, sofisticación y respeto por el medio ambiente. Algunas de las opciones de gestión y políticas sugeridas para mitigar los impactos de las aguas residuales de la acuicultura en el medio ambiente son las mejoras en la calidad de los piensos y los métodos de alimentación y la intervención del gobierno a través de sus agencias. Esta revisión sugiere un plan de gestión de aguas residuales de acuicultura de trípode que involucra a los acuicultores, agencias gubernamentales e instituciones de investigación, de modo que las aguas residuales de la acuicultura se traten antes de ser descargadas en los cuerpos de aguas continentales, las agencias gubernamentales se aseguren de que los acuicultores cumplan con las políticas y regulaciones sobre gestión de residuos, y las instituciones de investigación desarrollen tecnologías locales mejoradas y rentables para tratar las aguas residuales de la acuicultura.
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining

Foundation models have reshaped the landscape of Remote Sensing (RS) by enhancing various image interpretation tasks. Pretraining is an active research topic, encompassing supervised and self-supervised learning methods to initialize model weights effectively. However, transferring the pretrained models to downstream tasks may encounter task discrepancy due to their formulation of pretraining as image classification or object discrimination tasks. In this study, we explore the Multi-Task Pretraining (MTP) paradigm for RS foundation models to address this issue. Using a shared encoder and task-specific decoder architecture, we conduct multi-task supervised pretraining on the SAMRS dataset, encompassing semantic segmentation, instance segmentation, and rotated object detection. MTP supports both convolutional neural networks and vision transformer foundation models with over 300 million parameters. The pretrained models are finetuned on various RS downstream tasks, such as scene classification, horizontal and rotated object detection, semantic segmentation, and change detection. Extensive experiments across 14 datasets demonstrate the superiority of our models over existing ones of similar size and their competitive performance compared to larger state-of-the-art models, thus validating the effectiveness of MTP.
Sr, Nd and Pb isotope and trace element geochemistry of the New England seamount chain

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric and Planetary Sciences, 1984. ; Bibliography: leaves 78-86. ; by Brian Daniel Taras. ; M.S.
Towards the Study of Morphological Processing of the Tangkhul Language

There is no or little work on natural language processing of Tangkhul language. The current work is a humble beginning of morphological processing of this language using an unsupervised approach. We use a small corpus collected from different sources of text books, short stories and articles of other topics. Based on the experiments carried out, the morpheme identification task using morphessor gives reasonable and interesting output despite using a small corpus.
Equity in environmental governance: perceived fairness of distributional justice principles in marine co-management

Abstract   Concerns with distributional justice invariably arise in environmental governance, especially in the conservation and management of common-pool resources. These initiatives generate an array of costs and benefits that are typically heterogeneously distributed. Distribution of these impacts in a way that is considered fair by local stakeholders is not only a moral imperative, but instrumental to achieving social and ecological success given perceived unfairness fosters conflict and undermines cooperation. However, understandings of local stakeholders’ conceptions of distributional fairness are rare because research often assesses distributional outcomes based on tacit assumptions about what constitutes fairness (e.g. equality). We examine what local stakeholders consider distributional fairness with respect to monetary benefits arising from a collective payment for ecosystem services scheme in a co-managed marine protected area in Fiji. In six villages associated with the co-managed marine protected area, we elicited individuals’ fairness judgements of five distributional justice principles: equality, need, and three forms of proportionality based on customary rights, fisheries opportunity-costs, and involvement in co-management. We examine how fairness judgements are associated with socio-demographic characteristics indicative of key identities, thereby building on socially-aggregated approaches typical of the nascent literature on perceived fairness. We find the rights-based principle was considered the ‘most fair’ and the opportunity-costs principle the ‘least fair’. Our findings challenge prevailing understandings of distributional justice in conservation and commons management, which favour the principles of equality or opportunity-cost. We also find that education was significantly positively related to fairness judgements of all principles, whilst wealth was significantly related to the equality and the opportunity-based principles. These results provide insights into how fairness judgements could be influenced by key elements of current social change in the Global South (e.g. increasing formal education, market engagement and wealth accumulation). Overall, our results suggest that fair environmental governance requires explicit identification of distributional fairness conceptions of those most affected by such initiatives, especially in a context of increasing globalisation of conservation knowledge and practice.
A Generalized Level Set-Navier Stokes Numerical Method for Predicting Thermo-Fluid Dynamics of Turbulent Free Surface

In the present paper, a new generalized level set numerical method based on the Fast Marching Method is developed for predicting the moving interface thermo-fluid dynamics in turbulent free surface flows. The numerical method is devoted to predict the turbulent interfacial dynamics resulting from either aerodynamic force or thermocapillary effects. The unsteady Reynolds averaged Navier-Stokes equations (RANS) and energy equation are coupled with the level set method and solved separately in each phase using the finite volume method on a non-staggered grid system. The application of the fast marching technique enables the fast as well as the accurate transport of the moving interface via the extension velocity algorithm and provides, simultaneously, robust and precise modeling of the interfacial normal and tangential stresses resulting from surface curvature and Marangoni effects, respectively. The Reynolds stresses are estimated by solving the standard two-equation k-e turbulence model. A wide range of validation and benchmark cases in different flow regimes are performed and their results are compared with the previous published data in order to assist the accuracy of the developed numerical method. In general, the developed numerical method indicates a remarkable capability in predicting the interfacial thermo-fluid dynamics of moving interfaces in different free surface flow problems encountered in a wide range of industrial and engineering applications.
Exploring biological and chemical control methods in an integrated pest management approach for Varroa destructor in honey bee (Apis mellifera) colonies

Honey bees suffer from parasitism from Varroa destructor, which spreads between colonies via several transmission routes. Mites infest the brood cells of developing bees, feeding on and transmitting pathogens to their hosts. When mites are inside capped brood cells, they are protected from beekeeper applied acaricides. In this study, I used indoor storage to halt brood production, with the goal of reducing the protective brood cells and force mites into a phoretic state to increase susceptibility to treatment. I tested the efficacy of a novel strain of an entomopathogenic Metarhizium fungus as a mite control method against oxalic acid (OA). I observed that indoor storage effectively reduced the quantity of capped brood. However, I did not observe a proportional associated increase in phoretic mite population. Metarhizium reduced Varroa populations at similar rates when compared with OA, but neither OA nor Metarhizium performed significantly better after indoor storage compared to outdoor storage. This research shows promise for novel tools to reduce mite infestations and combat pesticide resistance when treating V. destructor.
The Application of Supply Chain Risk Management Assessment in Smallscale Fisheries in Bangka Belitung, Indonesia Using Probabilistic Risk Analysis (PRA) Method

Indonesia’s small-scale fisheries contributed as the second large fishing country which create an economy of scale throughout the food security. However, fish capturing from the indigenous livelihood weighed an inefficiency on the production volume due to limited resources and knowledge. The research aims to benefit by applying supply chain risk management on fishery products in Bangka Belitung, Indonesia across its regencies with product-hub placement. The objective is to identify the local risk distributions and most vital causes to cumulative losses for specific fish commodities. The research would specify the least to most common risk occurred. The research is a triangulation method consisting of probabilistic risk analysis, interviews, and direct observations. The result showed there is a significant level of risk outspread around each municipality in Bangka Belitung, showing from the capture, sampling, and fishery businesses production data. The lead time in days and price per unit became the two main factors as it validates the risk occurrence. The government strategy was limited on the high number of volume and potentials, a case would be shrimps. Indeed, there is an indication that high risks are occurring in most small lead time fishery businesses across Bangka Belitung with mackerel fish as the main spoilage, followed by crab, and yellow-tail scads. The findings showed there is an average of 35,00% risk inside 30,36% fishery businesses in Bangka Belitung and the risk impact per business capture ranged between 0,33 to 0,77 probability. The total risk for price reached 94.78% of the total fish commodities. Keywords—Probabilistic Risk Analysis; Product-Hub; Risk Management; Small-Scale Fisheries; Supply Chain
Correction to: Development of Guanfacine Extended-Release Dosing Strategies in Children and Adolescents with ADHD Using a Physiologically Based Pharmacokinetic Model to Predict Drug–Drug Interactions with Moderate CYP3A4 Inhibitors or Inducers

The article "Development of Guanfacine Extended-Release Dosing Strategies in Children and Adolescents with ADHD Using a PhysiologicallyBased Pharmacokinetic Model to Predict Drug-Drug Interactions with Moderate CYP3A4 Inhibitors or Inducers", written by Aiqun Li, Karen Yeo, Devin Welty, Haojing Rong, was originally published electronically on the publisher's internet portal (currently SpringerLink) on 02nd November, 2017 without open access.
Flag fault-tolerant error correction, measurement, and quantum computation for cyclic CSS codes

Flag qubits have recently been proposed in syndrome extraction circuits to detect high-weight errors arising from fewer faults. The use of flag qubits allows the construction of fault-tolerant protocols with the fewest number of ancillas known to-date. In this work, we prove some critical properties of CSS codes constructed from classical cyclic codes that enable the construction of a flag fault-tolerant error correction scheme. We then develop fault-tolerant protocols as well as a family of circuits for flag fault-tolerant error correction and operator measurement, requiring only four ancilla qubits and applicable to cyclic CSS codes of distance 3. The measurement protocol can be further used for logical Clifford gate implementation via quantum gate teleportation. We also provide examples of cyclic CSS codes with large encoding rates.
Indrani Sigamany,                     <i>Nomadic Indigenous Peoples and the Law: Self-determination, Land Rights and Gender Justice in India</i>

This article was published open access under a CC BY-NC 4.0 licence:                     https://creativecommons.org/licenses/by-nc/4.0/                     .
Bayesian deep reinforcement learning for uncertainty quantification and adaptive support optimization in deep foundation pit engineering

Abstract           This study develops a novel framework integrating Bayesian inference with deep reinforcement learning for uncertainty quantification and adaptive support optimization in multi-physics coupled deep foundation pit systems. The methodology systematically incorporates prior knowledge and real-time monitoring observations through Markov Chain Monte Carlo updating to refine parameter estimates while employing deep reinforcement learning algorithms for autonomous support optimization. A comprehensive multi-physics coupled numerical model captures mechanical-hydraulic-thermal interdependencies with explicit coupling mechanisms and Shanghai-specific soil characterization. Validation through a representative Shanghai deep foundation pit project demonstrates superior performance with prediction accuracy (R2 = 0.91), reliability quantification (coverage probability = 96.8%), and practical improvements including 35% reduction in maximum wall displacement (from 45.8 to 29.7 mm), 42% decrease in surface settlement (from 28.5 to 16.5 mm), and 18% cost savings (¥2.3 million) compared to conventional deterministic approaches. The intelligent system achieved zero safety incidents, 12% construction duration reduction, and enhanced deformation control through real-time adaptive support adjustments including optimized prestressing forces and strategic anchor installations. The research contributes essential theoretical foundations and practical tools for advancing intelligent construction practices in complex urban geotechnical engineering applications.
Blind source separation methods for deconvolution of complex signals in cancer biology

Two blind source separation methods (Independent Component Analysis and Non-negative Matrix Factorization), developed initially for signal processing in engineering, found recently a number of applications in analysis of large-scale data in molecular biology. In this short review, we present the common idea behind these methods, describe ways of implementing and applying them and point out to the advantages compared to more traditional statistical approaches. We focus more specifically on the analysis of gene expression in cancer. The review is finalized by listing available software implementations for the methods described.
Efficient separate quantification of state preparation errors and measurement errors on quantum computers and their mitigation

Current noisy quantum computers have multiple types of errors, which can occur in the state preparation, measurement/readout, and gate operation, as well as intrinsic decoherence and relaxation. Partly motivated by the booming of intermediate-scale quantum processors, measurement and gate errors have been recently extensively studied, and several methods of mitigating them have been proposed and formulated in software packages (e.g., in IBM Qiskit). Despite this, the state preparation error and the procedure to quantify it have not yet been standardized, as state preparation and measurement errors are usually considered not directly separable. Inspired by a recent work of Laflamme, Lin, and Mor \cite{laflamme2022algorithmic}, we propose a simple and resource-efficient approach to quantify separately the state preparation and readout error rates. With these two errors separately quantified, we also propose methods to mitigate them separately, especially mitigating state preparation errors with linear (with the number of qubits) complexity. As a result of the separate mitigation, we show that the fidelity of the outcome can be improved by an order of magnitude compared to the standard measurement error mitigation scheme. We also show that the quantification and mitigation scheme is resilient against gate noise and can be immediately applied to current noisy quantum computers. To demonstrate this, we present results from cloud experiments on IBM&amp;apos;s superconducting quantum computers. The results indicate that the state preparation error rate is also an important metric for qubit metrology that can be efficiently obtained.