ethicalabs/Research-Intent-Collab huggingface dataset:
Deep Generative Models for Ultra-High Granularity Particle Physics Detector Simulation: A Voyage From Emulation to Extrapolation

Simulating ultra-high-granularity detector responses in Particle Physics represents a critical yet computationally demanding task. This thesis aims to overcome this challenge for the Pixel Vertex Detector (PXD) at the Belle II experiment, which features over 7.5M pixel channels-the highest spatial resolution detector simulation dataset ever analysed with generative models. This thesis starts off by a comprehensive and taxonomic review on generative models for simulating detector signatures. Then, it presents the Intra-Event Aware Generative Adversarial Network (IEA-GAN), a new geometry-aware generative model that introduces a relational attentive reasoning and Self-Supervised Learning to approximate an event in the detector. This study underscores the importance of intra-event correlation for downstream physics analyses. Building upon this, the work drifts towards a more generic approach and presents YonedaVAE, a Category Theory-inspired generative model that tackles the open problem of Out-of-Distribution (OOD) simulation. YonedaVAE introduces a learnable Yoneda embedding to capture the entirety of an event based on its sensor relationships, formulating a Category theoretical language for intra-event relational reasoning. This is complemented by introducing a Self-Supervised learnable prior for VAEs and an Adaptive Top-q sampling mechanism, enabling the model to sample point clouds with variable intra-category cardinality in a zero-shot manner. Variable Intra-event cardinality has not been approached before and is vital for simulating irregular detector geometries. Trained on an early experiment data, YonedaVAE can reach a reasonable OOD simulation precision of a later experiment with almost double luminosity. This study introduces, for the first time, the results of using deep generative models for ultra-high granularity detector simulation in Particle Physics.
The development of a material model and wheel–tissue interaction for simulating wheeled surgical robot mobility

In vivo surgical robot wheel and tissue interaction was studied using a nonlinear finite element model. A liver material model, derived from laboratory experiments, was implemented as a viscoelastic material. A finite element simulation of this laboratory test confirmed the accuracy of the liver material model. This material model was then used as the tissue model to study wheel performance. A helical wheel moving on the liver model was used to replicate laboratory experiments that included several different slip ratios and applied loads. The drawbar force produced in this model showed good agreement with the physical tests. These results have provided the baseline for studying how changes in wheel geometry, such as tread height, tread spacing and wheel diameter, affect drawbar force and ultimately wheel performance. These results will be used in future surgical robot wheel designs.
Additional file 1: of Toward the precision breast cancer survival prediction utilizing combined whole genome-wide expression and somatic mutation analysis

PATHER significantly enriched terms base on 118 survival related genes. (DOCX 15Â kb)
CIGR Handbook of Agricultural Engineering, Volume I Land and Water Engineering, Chapter 5 Irrigation and Drainage, Part 5.4 Irrigation Methods

First paragraph: Irrigation has been practiced for millennia. Until the 20th century, all irrigation depended on gravity to deliver water to the fields and to spread water across the surface of the land. Development of efficient engines, pumps, and impact sprinklers in the first half of this century allowed farmers to mimic rainfall with sprinkler irrigation. In the past 20 years, microirrigation has become more common where water is scarce, crop values are high, and the technology is practical. Surface irrigation remains the dominant system in use worldwide, although sprinkler irrigation has become widely used in some areas. Total irrigated areas in theWorld are given in Table 5.3.An estimate of the percentages of the three primary methods of irrigation in four regions is presented in Table 5.4. Data in the table cannot be extrapolated to world figures because the data are not available for most regions, particularly Asia, which represents 69% of the world’s irrigated area and where surface irrigation is predominant.
Privacy‐Preserving Federated Learning: Adaptive Quantization and Layer‐Specific Differential Privacy With Client Dropout Mitigation

This paper presents an enhanced federated learning architecture that addresses key challenges in distributed machine learning through three novel contributions: (1) a theoretically grounded sensitivity analysis for differential privacy that formally derives the Δ parameter for deep learning models, (2) an adaptive quantization scheme that dynamically adjusts to model architecture and layer importance, and (3) a client dropout mitigation strategy using weighted aggregation and historical model averaging. We evaluate our framework on four benchmark datasets, demonstrating superior performance in a unified comparative analysis over FATE and PySyft frameworks. The system integrates AES, RSA, and TLS encryption with differential privacy in a novel framework that maintains model accuracy alongside strong privacy guarantees. We provide a comprehensive theoretical analysis of the sensitivity parameter Δ for convolutional neural networks, demonstrating its dependence on layer depth and gradient norms. Our adaptive quantization approach shows 15%–20% higher compression efficiency compared to uniform quantization while maintaining model accuracy. Experimental results on MNIST, CIFAR‐10, CIFAR‐100, and Fashion‐MNIST demonstrate the system’s effectiveness, achieving accuracies of 98.5%, 85.3%, 65.5%, and 92.1%, respectively, while maintaining ϵ‐differential privacy with ϵ values between 0.3 and 1.0, with formal (ε, δ)‐differential privacy guarantees tracked via the moments accountant method. The proposed client dropout handling method reduces accuracy degradation by up to 40% compared to standard federated averaging under 30% client dropout rates. Comparative analysis with FATE and PySyft shows our approach achieves 16−17% better communication efficiency while maintaining comparable privacy guarantees.
Supervision of Implementation: Dispute settlement of the World Trade Organization (WTO)

This entry provides an analysis of the rules governing the supervision of implementation of Dispute Settlement Body (“DSB”) reports based on the World Trade Organization’s (“WTO”) Dispute Settlement Understanding (“DSU”). Specifically, it focuses on the precise functions of the DSB’s implementation surveillance after an Appellate Body (“AB”) or Panel Report has been issued. As such, this entry does not analyze procedures developed under Article 21:5 DSU nor procedures developed under Article 22:6 DSU, because those provisions concern interactions with Members prior to implementation and other elements of WTO law. Rather, this entry analyzes the rules and procedures that govern the DSB’s follow-up on whether its reports have been implemented and situations where retaliation measures are implemented.
Detection Rates of Artificial Intelligence–Generated Content in Scholarly Publishing before and after ChatGPT

The use of artificial intelligence in scholarly publishing is quickly becoming a focal point as researchers, journal editors, and publishers determine how to balance the benefits of AI with the potential ethical drawbacks. We used four different AI text detectors to analyze one hundred articles published in economics journals in 2019, before the release of ChatGPT, and one hundred articles from the same journals published in 2023–24, after the release of ChatGPT. Using the AI likelihood scores generated from each detector as the dependent variable and controlling for the number of authors, word count, and journal fixed effects, we find that only ZeroGPT had AI likelihood scores that were 3.89 percentage points higher in the post-AI papers compared to the pre-AI papers; however, this result was only statistically significant at the 90 per cent level. The other AI detectors, Originality, Crossplag, and Winston, showed that pre- and post-AI papers had AI scores that were not statistically different when controlling for other factors. We also find that there is little to no correlation between the scores produced by the four detectors when scanning the same papers. This research highlights the fallibility of accurate AI detection and the need for further research as a foundation for developing future AI policies in scholarly publishing.
Robust integration of external control data in randomized trials

One approach for increasing the efficiency of randomized trials is the use of "external controls" -- individuals who received the control treatment studied in the trial during routine practice or in prior experimental studies. Existing external control methods, however, can be biased if the populations underlying the trial and the external control data are not exchangeable. Here, we characterize a randomization-aware class of treatment effect estimators in the population underlying the trial that remain consistent and asymptotically normal when using external control data, even when exchangeability does not hold. We consider two members of this class of estimators: the well-known augmented inverse probability weighting trial-only estimator, which is the efficient estimator when only trial data are used; and a potentially more efficient member of the class when exchangeability holds and external control data are available, which we refer to as the optimized randomization-aware estimator. To achieve robust integration of external control data in trial analyses, we then propose a combined estimator based on the efficient trial-only estimator and the optimized randomization-aware estimator. We show that the combined estimator is consistent and no less efficient than the most efficient of the two component estimators, whether the exchangeability assumption holds or not. We examine the estimators' performance in simulations and we illustrate their use with data from two trials of paliperidone extended-release for schizophrenia.
Cost-Effectiveness of Transcatheter Aortic Valve Implantation Using a Balloon-Expandable Valve in Japan: Experience From the Japanese Pilot Health Technology Assessment

Transcatheter aortic valve implantation (TAVI) is an innovative and effective treatment in high-surgical-risk (HR) and inoperable patients with symptomatic severe aortic stenosis.This cost-effectiveness analysis of transfemoral TAVI (TF-TAVI) compared with surgical aortic valve replacement (SAVR) conforms with the methodological guidelines for cost-effectiveness evaluation by the Ministry of Health, Labor, and Welfare in Japan.The cost-effectiveness of TF-TAVI using SAPIEN XT was evaluated using a lifetime Markov simulation from the national payer perspective. Comparators were SAVR for HR patients and standard of care (SOC) for inoperable patients. A systematic literature review for clinical evidence of TF-TAVI and comparators was conducted. The evidence for TF-TAVI was derived from the SOURCE XT registry and Japanese post marketing surveillance. Because there was no literature directly or indirectly comparing TF-TAVI using SAPIEN XT with comparators, the comparator data were selected from relevant published studies, considering the similarity of study eligibility criteria and patient backgrounds (eg, age and surgical risk scores). Sensitivity analyses were used to validate the robustness of results.The incremental cost-effectiveness ratio of TF-TAVI versus SAVR for HR patients was ¥1.3 million/quality-adjusted life-years (QALYs). The incremental cost-effectiveness ratio of TF-TAVI versus SOC for inoperable patients was ¥3.5 million/QALY.TF-TAVI was cost-effective when compared with SAVR for HR patients and when compared with SOC for inoperable patients, using a threshold of ¥5 million/QALY.
SITE SUITABILITY ANALYSIS FOR BAY SCALLOP AQUACULTURE AND IMPLICATIONS FOR SUSTAINABLE FISHERIES MANAGEMENT IN THE HA LONG BAY ARCHIPELAGO, NORTHERN VIETNAM

Mollusc culture if properly managed, may help decrease capture fisheries over-exploitation in Vietnam, and possibly become an alternative income for local fishermen. The definition and characterization of zones suitable for aquaculture is pivotal for its success and sustainable development, and this study aims at determining the suitability of Argopecten irradians (Bay scallop) culture in the Ha Long Bay Archipelago. Temperature, salinity, chlorophyll-a, total suspended solid and bathymetry, were compiled in an environmental suitability model. Distance of culture sites from landing points and fish markets were instead grouped in an infrastructural suitability model. In both models, developed with Geographic Information Systems, the suitability scores were ranked on a scale from 1 (unsuitable) to 6 (very-highly suitable). Results showed that 98 % of the studied area is environmentally suitable for such culture. However, overlaying the infrastructural factors the suitable zone decrease to 38 %. Advantages and disadvantages of two management options were then discussed: (a) strengthening fisheries infrastructures or (b) developing post harvesting processing plants.
Cosmic ray modulation studies in the outer heliosphere

Abstract   During the last decade, the Pioneer 10 and 11, and Voyager 1 and 2 missions have greatly expanded our understanding of the structure and extent of the outer heliosphere. In particular, studies of the solar modulation of galactic cosmic rays in this heliosphere have benefited enormously from these missions. Our current understanding of this modulation mechanism, mainly in terms of numerical solutions of the Parker transport equation, is briefly reviewed in this paper. The first crossing by one of these four spacecraft of the termination shock of the heliosphere is eagerly awaited, and much of the present work is done in anticipation of this event.
Cross-validation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods

We introduce a framework to build a survival/risk bump hunting model with a censored time-to-event response. Our Survival Bump Hunting (SBH) method is based on a recursive peeling procedure that uses a specific survival peeling criterion derived from non/semi-parametric statistics such as the hazards-ratio, the log-rank test or the Nelson-Aalen estimator. To optimize the tuning parameter of the model and validate it, we introduce an objective function based on survival or prediction-error statistics, such as the log-rank test and the concordance error rate. We also describe two alternative cross-validation techniques adapted to the joint task of decision-rule making by recursive peeling and survival estimation. Numerical analyses show the importance of replicated cross-validation and the differences between criteria and techniques in both low and high-dimensional settings. Although several non-parametric survival models exist, none addresses the problem of directly identifying local extrema. We show how SBH efficiently estimates extreme survival/risk subgroups unlike other models. This provides an insight into the behavior of commonly used models and suggests alternatives to be adopted in practice. Finally, our SBH framework was applied to a clinical dataset. In it, we identified subsets of patients characterized by clinical and demographic covariates with a distinct extreme survival outcome, for which tailored medical interventions could be made. An R package `PRIMsrc` is available on CRAN and GitHub.
The CORA dataset: validation and diagnostics of in-situ ocean temperature and salinity measurements

Abstract. The French program Coriolis, as part of the French operational oceanographic system, produces the COriolis dataset for Re-Analysis (CORA) on a yearly basis. This dataset contains in-situ temperature and salinity profiles from different data types. The latest release CORA3 covers the period 1990 to 2010. Several tests have been developed to ensure a homogeneous quality control of the dataset and to meet the requirements of the physical ocean reanalysis activities (assimilation and validation). Improved tests include some simple tests based on comparison with climatology and a model background check based on a global ocean reanalysis. Visual quality control is performed on all suspicious temperature and salinity profiles identified by the tests, and quality flags are modified in the dataset if necessary. In addition, improved diagnostic tools have been developed – including global ocean indicators – which give information on the quality of the CORA3 dataset and its potential applications. CORA3 is available on request through the MyOcean Service Desk (http://www.myocean.eu/).
Frequency Ratio Measurements with 18-digit Accuracy Using a Network of Optical Clocks

Atomic clocks occupy a unique position in measurement science, exhibiting higher accuracy than any other measurement standard and underpinning six out of seven base units in the SI system. By exploiting higher resonance frequencies, optical atomic clocks now achieve greater stability and lower frequency uncertainty than existing primary standards. Here, we report frequency ratios of the $^{27}$Al$^+$, $^{171}$Yb and $^{87}$Sr optical clocks in Boulder, Colorado, measured across an optical network spanned by both fiber and free-space links. These ratios have been evaluated with measurement uncertainties between $6\times10^{-18}$ and $8\times10^{-18}$, making them the most accurate reported measurements of frequency ratios to date. This represents a critical step towards redefinition of the SI second and future applications such as relativistic geodesy and tests of fundamental physics.
Transforming Vulnerability into Resilience: Strategies for Climate Adaptation

Abstract:   Climate change poses significant threats to natural ecosystems, livelihoods, and human well-being, particularly in vulnerable regions. This paper explores the concept of environmental resilience as a crucial framework for transitioning from vulnerability to sustainability. By examining adaptive strategies, community-based responses, and policy interventions, the study highlights how ecosystems and societies can absorb climatic shocks and recover more effectively. Special attention is given to sustainable practices that enhance resilience, such as ecosystem-based adaptation, water conservation, and renewable energy integration. The paper also addresses the role of education, local governance, and indigenous knowledge in fostering long-term environmental resilience. Drawing from both global and local case studies, the research emphasizes the need for inclusive, proactive, and science-based approaches to strengthen resilience against climate impacts. Ultimately, the study advocates for a resilience-focused development model that aligns with environmental sustainability and climate justice.
High performance computational chemistry: Towards fully distributed parallel algorithms

An account is given of work in progress within the High Performance Computational Chemistry Group (HPCC) at the Pacific Northwest Laboratory (PNL) to develop molecular modeling software applications for massively parallel processors (MPPs). A discussion of the issues in developing scalable parallel algorithms is presented, with a particular focus on the distribution, as opposed to the replication, of key data structures. Replication of large data structures limits the maximum calculation size by imposing a low ratio of processors to memory. Only applications that distribute both data and computation across processors are truly scalable. The use of shared data structures, which may be independently accessed by each process even in a distributed-memory environment, greatly simplifies development and provides a significant performance enhancement. In describing tools to support this programming paradigm, an outline is given of the implementation and performance of a highly efficient and scalable algorithm to perform quadratically convergent, self-consistent field calculations on molecular systems. A brief account is given of the development of corresponding MPP capabilities in the areas of periodic Hartree Fock, Moeller-Plesset perturbation theory (MP2), density functional theory, and molecular dynamics. Performance figures are presented using both the Intel Touchstone Delta and Kendall Square Research KSR-2 supercomputers.
Lensing power spectrum of the cosmic microwave background with deep polarization experiments

10 pages, 7 figures, submitted to PRD
The Adoption and Use of Human Resource Information System (HRIS) in Ghana

The study looked at the adoption of Human Resource Information System (HRIS) among Ghanaian firms. A survey was conducted on 129 firms out of the 150 samples randomly selected from both the public and the private sectors in the country with a response rate of 86%. The findings first revealed that the adoption rate of HRIS in enterprises is not a common practice in Ghana since two-thirds of the organizations have never adopted HRIS use. Major general denominators for adoption and use of HRIS include firm size, organization type (i.e. profit making limited liability companies and profit making government organization) and age as well as the industry to which firms belong. Firms attributed the slow rate of adoption to reasons including the low numbers of employees, high cost of system installation, unawareness and low priority for such a system. Again, it was realized that the companies??? readiness to adopt such a system was not encouraging. There were some technical, organizational and environmental factors that affect HRIS adoption which were unearthed.
Transaction Costs And Optimal Number Of Suppliers For Transport Logistics Using Electronic Commerce Technologies

A fundamental change in supplier base management has been under way in the industry in recent years. Since 1991, the supplier base has been reduced significantly (by 50% or more) across all sectors of the industry. Many firms have taken proactive steps to consolidate and restructure their supplier networks in order to reduce cost, improve quality, and strengthen their competitiveness. A major change has been the delegation of greater responsibilities to key suppliers, such as the production of major parts and components, laboratory and inspection functions, and management of lower tier suppliers. The reduction in the supplier base, rather than being confined to the upper-tiers, appears to have permeated all layers of the industry. The paper investigates the transactions costs and optimal number of suppliers for transport logistics using electronic commerce technologies
Understanding Public Responses to AI-generated Visual Art: A Topic and Emotion Analysis of Social Media Comments Data

This study analyzes the comments on AI-generated visual art on social media, focusing on emotional and thematic aspects. With the rise of AI-generated content on social media platforms such as DALL·E and Midjourney, AI art has gained both positive and negative attention. This mixed-methods study uses emotion analysis and thematic modeling to investigate the audience's response to the art of AI-generation. The study uses two sets of frameworks: Machine-Driven Classification of Open-Ended Responses (MDCOR) and Sentiment and Emotion Network Analysis (SENA) to classify and analyze social media comments to grasp the emotional tone of the discussion and AI art-related issues. The data shows that the social media debate about authenticity, author identity and whether AI will replace human artists presents a complex picture of enthusiasm, doubt and worry. The study also found that the public's impression will change in the process of interacting with AI art. This study provides a comprehensive framework for understanding public opinion and lays the foundation for further investigation of the social and cultural impact of AI on art and creativity.