dyfan/halluhard-seed-questions huggingface dataset:
A joint measurement is presented of the branching fractions $B^0_s\toμ^+μ^-$ and $B^0\toμ^+μ^-$ in proton-proton collisions at the LHC by the CMS and LHCb experiments. The data samples were collected in 2011 at a centre-of-mass energy of 7 TeV, and in 2012 at 8 TeV. The combined analysis produces the first observation of the $B^0_s\toμ^+μ^-$ decay, with a statistical significance exceeding six standard deviations, and the best measurement of its branching fraction so far. Furthermore, evidence for the $B^0\toμ^+μ^-$ decay is obtained with a statistical significance of three standard deviations. The branching fraction measurements are statistically compatible with SM predictions and impose stringent constraints on several theories beyond the SM.

Research question: How do precise measurements of rare meson decays into muon pairs constrain theories beyond the Standard Model, and which classes of new-physics models are most strongly affected?
Despite the advances of deep learning in specific tasks using images, the principled assessment of image fidelity and similarity is still a critical ability to develop. As it has been shown that Mean Squared Error (MSE) is insufficient for this task, other measures have been developed with one of the most effective being Structural Similarity Index (SSIM). Such measures can be used for subspace learning but existing methods in machine learning, such as Principal Component Analysis (PCA), are based on Euclidean distance or MSE and thus cannot properly capture the structural features of images. In this paper, we define an image structure subspace which discriminates different types of image distortions. We propose Image Structural Component Analysis (ISCA) and also kernel ISCA by using SSIM, rather than Euclidean distance, in the formulation of PCA. This paper provides a bridge between image quality assessment and manifold learning opening a broad new area for future research.

Research question: How can dimensionality reduction or subspace learning methods be adapted to use perceptual image similarity measures (like SSIM) instead of Euclidean/MSE-based distances, and what are the practical benefits and challenges of doing so?
The last decade has seen an explosion in models that describe phenomena in systems medicine. Such models are especially useful for studying signaling pathways, such as the Wnt pathway. In this chapter we use the Wnt pathway to showcase current mathematical and statistical techniques that enable modelers to gain insight into (models of) gene regulation, and generate testable predictions. We introduce a range of modeling frameworks, but focus on ordinary differential equation (ODE) models since they remain the most widely used approach in systems biology and medicine and continue to offer great potential. We present methods for the analysis of a single model, comprising applications of standard dynamical systems approaches such as nondimensionalization, steady state, asymptotic and sensitivity analysis, and more recent statistical and algebraic approaches to compare models with data. We present parameter estimation and model comparison techniques, focusing on Bayesian analysis and coplanarity via algebraic geometry. Our intention is that this (non exhaustive) review may serve as a useful starting point for the analysis of models in systems medicine.

Research question: What are the main challenges in estimating parameters for ordinary differential equation models in systems medicine, and how can Bayesian approaches help address them?
Recent developments have renewed the demand for solar cells with increased tolerance to radiation damage. To investigate the specific irradiation damage of 1 MeV electron irradiation in GaInAsP lattice matched to InP for varying In and P contents, a simulation based analysis is employed: by fitting the quantum efficiency and open-circuit voltage simultaneously before and after irradiation, the induced changes in lifetime are detected. Furthermore, the reduction of irradiation damage during regeneration under typical satellite operating conditions for GEO missions (60°C and AM0 illumination) is investigated. A clear decrease of the radiation damage is observed after post irradiation regeneration. This regeneration effect is stronger for increasing InP-fraction. It is demonstrated that the irradiation induced defect recombination coefficient for irradiation with 1 MeV electrons after regeneration for 216 hours can be described with a linear function of InP-fraction between 1*10$^{-5}$ cm$^2$/s for GaAs and 7*10$^{-7}$ cm$^2$/s for InP. The results show that GaInAsP is a promising material for radiation hard space solar cells.

Research question: What physical mechanisms enable thermal and light-assisted regeneration (annealing) of irradiation-induced defects in III–V multinary solar cell materials, and how does alloy composition typically influence the effectiveness of such regeneration?
Xenon can produce general anesthesia. Its main protein target is the N-methyl-D-aspartate receptor, a ionotropic channel playing a pivotal role in the function of the central nervous system.
  The molecular mechanisms allowing this noble gas to have such a specific effect remain obscure, probably as a consequence of the lack of structural data at the atomic level of detail. Herein, as a result of five independent molecular dynamics simulations, three different binding sites were found for xenon in the glycine binding domain of the N-methyl-D-aspartate receptor. The absolute binding free energy of xenon in these sites ranges between -8 and -14 kJ/mole. However, it depends significantly upon the protein conformer chosen for performing the calculation, suggesting that larger values could probably be obtained, if other conformers were considered.
  These three sites are next to each other, one of them being next to the glycine site. This could explain why the F758W and F758Y mutations can prevent competitive inhibition by xenon without affecting glycine binding.

Research question: How can an inert, nonpolar atom like xenon selectively bind to and modulate the function of an ionotropic receptor in the central nervous system?
The derivation trees of a tree adjoining grammar provide a first insight into the sentence semantics, and are thus prime targets for generation systems. We define a formalism, feature-based regular tree grammars, and a translation from feature based tree adjoining grammars into this new formalism. The translation preserves the derivation structures of the original grammar, and accounts for feature unification.

Research question: How do feature-based regular tree grammars compare to traditional tree adjoining grammars in representing derivation structures and handling feature unification, and what practical advantages do they offer for generation systems?
Diabetic retinopathy (DR) is a diabetes complication that affects eyes. DR is a primary cause of blindness in working-age people and it is estimated that 3 to 4 million people with diabetes are blinded by DR every year worldwide. Early diagnosis have been considered an effective way to mitigate such problem. The ultimate goal of our research is to develop novel machine learning techniques to analyze the DR images generated by the fundus camera for automatically DR diagnosis. In this paper, we focus on identifying small lesions on DR fundus images. The results from our analysis, which include the lesion category and their exact locations in the image, can be used to facilitate the determination of DR severity (indicated by DR stages). Different from traditional object detection for natural images, lesion detection for fundus images have unique challenges. Specifically, the size of a lesion instance is usually very small, compared with the original resolution of the fundus images, making them diffcult to be detected. We analyze the lesion-vs-image scale carefully and propose a large-size feature pyramid network (LFPN) to preserve more image details for mini lesion instance detection. Our method includes an effective region proposal strategy to increase the sensitivity. The experimental results show that our proposed method is superior to the original feature pyramid network (FPN) method and Faster RCNN.

Research question: What are the main challenges and recommended best practices for developing and validating machine learning systems that reliably detect very small lesions in high-resolution retinal fundus images across different cameras and patient populations?
The progress of some AI paradigms such as deep learning is said to be linked to an exponential growth in the number of parameters. There are many studies corroborating these trends, but does this translate into an exponential increase in energy consumption? In order to answer this question we focus on inference costs rather than training costs, as the former account for most of the computing effort, solely because of the multiplicative factors. Also, apart from algorithmic innovations, we account for more specific and powerful hardware (leading to higher FLOPS) that is usually accompanied with important energy efficiency optimisations. We also move the focus from the first implementation of a breakthrough paper towards the consolidated version of the techniques one or two year later. Under this distinctive and comprehensive perspective, we study relevant models in the areas of computer vision and natural language processing: for a sustained increase in performance we see a much softer growth in energy consumption than previously anticipated. The only caveat is, yet again, the multiplicative factor, as future AI increases penetration and becomes more pervasive.

Research question: What factors determine whether increasing model size causes higher inference energy consumption, and how can organizations estimate the real-world energy impact of deploying larger models at scale?
We present the results of processing the effects of the powerful Gamma Ray Burst GRB221009A captured by the charged particle detectors (electrostatic analyzers and solid-state detectors) onboard spacecraft at different points in the heliosphere on October 9, 2022. To follow the GRB221009A propagation through the heliosphere we used the electron and proton flux measurements from solar missions Solar Orbiter and STEREO-A; Earth magnetosphere and the solar wind missions THEMIS and Wind; meteorological satellites POES15, POES19, MetOp3; and MAVEN - a NASA mission orbiting Mars. GRB221009A had a structure of four bursts: less intense Pulse 1 - the triggering impulse - was detected by gamma-ray observatories at 131659 UT (near the Earth); the most intense Pulses 2 and 3 were detected on board all the spacecraft from the list, and Pulse 4 detected in more than 500 s after Pulse 1. Due to their different scientific objectives, the spacecraft, which data was used in this study, were separated by more than 1 AU (Solar Orbiter and MAVEN). This enabled tracking GRB221009A as it was propagating across the heliosphere. STEREO-A was the first to register Pulse 2 and 3 of the GRB, almost 100 seconds before their detection by spacecraft in the vicinity of Earth. MAVEN detected GRB221009A Pulses 2, 3, and 4 at the orbit of Mars about 237 seconds after their detection near Earth. By processing the time delays observed we show that the source location of the GRB221009A was at RA 288.5 degrees, Dec 18.5 degrees (J2000) with an error cone of 2 degrees

Research question: How can time-of-arrival differences measured by widely separated spacecraft be used to determine the sky location of a gamma‑ray burst, and what are the main sources of error or uncertainty in that triangulation method?
Tree frogs possess soft structured toe pads with channels that help squeeze out fluid from the region between the toe pad and the contacting surfaces. This structure enables them to walk on wet and rough surfaces. We present our preliminary result aiming at understanding the role of surface structure on hydrodynamic drainage forces. We have used the surface forces apparatus to measure the drainage forces (approach and retraction) in silicone oil. We compare the drainage force measured between two smooth PMMA surfaces with the one measure when one of the two surfaces has a structure with channels. We have observed that the presence of channels reduces the hydrodynamic drainage forces when the surfaces come together and reduces the adhesion when the surfaces are pulled apart. Our force measurements were compared to Reynolds theory and we discuss the possible role of elastohydrodynamic deformation in tree frog adhesion.

Research question: How do micro-scale surface channels alter the hydrodynamic drainage and resulting adhesion between compliant surfaces in viscous fluids, and what role does elastohydrodynamic deformation play in that process?
Distinguishing gastrointestinal stromal tumors (GISTs) from other intra-abdominal tumors and GISTs molecular analysis is necessary for treatment planning, but challenging due to its rarity. The aim of this study was to evaluate radiomics for distinguishing GISTs from other intra-abdominal tumors, and in GISTs, predict the c-KIT, PDGFRA,BRAF mutational status and mitotic index (MI). All 247 included patients (125 GISTS, 122 non-GISTs) underwent a contrast-enhanced venous phase CT. The GIST vs. non-GIST radiomics model, including imaging, age, sex and location, had a mean area under the curve (AUC) of 0.82. Three radiologists had an AUC of 0.69, 0.76, and 0.84, respectively. The radiomics model had an AUC of 0.52 for c-KIT, 0.56 for c-KIT exon 11, and 0.52 for the MI. Hence, our radiomics model was able to distinguish GIST from non-GISTS with a performance similar to three radiologists, but was not able to predict the c-KIT mutation or MI.

Research question: Can CT-based radiomics reliably predict tumor-specific genetic mutations and proliferation indices, or is biopsy-based molecular testing still required for accurate treatment planning?
Twisted bilayer graphene (TBG) is remarkable for its topological flat bands, which drive strongly-interacting physics at integer fillings, and its simple theoretical description facilitated by the Bistritzer-MacDonald Hamiltonian, a continuum model coupling two Dirac fermions. Due to the large moiré unit cell, TBG offers the unprecedented opportunity to observe reentrant Hofstadter phases in laboratory-strength magnetic fields near $25$T. This Letter is devoted to magic angle TBG at $2π$ flux where the magnetic translation group commutes. We use a newly developed gauge-invariant formalism to determine the exact single-particle band structure and topology. We find that the characteristic TBG flat bands reemerge at $2π$ flux, but, due to the magnetic field breaking $C_{2z} \mathcal{T}$, they split and acquire Chern number $\pm1$. We show that reentrant correlated insulating states appear at $2π$ flux driven by the Coulomb interaction at integer fillings, and we predict the characteristic Landau fans from their excitation spectrum. We conjecture that superconductivity can also be re-entrant at $2π$ flux.

Research question: How does applying a strong perpendicular magnetic field to a moiré two-dimensional material alter the topology and correlated phases of its low-energy electronic bands, and what experimental probes would best reveal those changes?
A joint measurement is presented of the branching fractions $B^0_s\toμ^+μ^-$ and $B^0\toμ^+μ^-$ in proton-proton collisions at the LHC by the CMS and LHCb experiments. The data samples were collected in 2011 at a centre-of-mass energy of 7 TeV, and in 2012 at 8 TeV. The combined analysis produces the first observation of the $B^0_s\toμ^+μ^-$ decay, with a statistical significance exceeding six standard deviations, and the best measurement of its branching fraction so far. Furthermore, evidence for the $B^0\toμ^+μ^-$ decay is obtained with a statistical significance of three standard deviations. The branching fraction measurements are statistically compatible with SM predictions and impose stringent constraints on several theories beyond the SM.

Research question: Why are measurements of rare neutral B-meson decays to muon pairs considered sensitive probes of physics beyond the Standard Model, and what types of new-physics scenarios can such measurements constrain?
This paper presents a novel approach to the technical analysis of wireheading in intelligent agents. Inspired by the natural analogues of wireheading and their prevalent manifestations, we propose the modeling of such phenomenon in Reinforcement Learning (RL) agents as psychological disorders. In a preliminary step towards evaluating this proposal, we study the feasibility and dynamics of emergent addictive policies in Q-learning agents in the tractable environment of the game of Snake. We consider a slightly modified settings for this game, in which the environment provides a "drug" seed alongside the original "healthy" seed for the consumption of the snake. We adopt and extend an RL-based model of natural addiction to Q-learning agents in this settings, and derive sufficient parametric conditions for the emergence of addictive behaviors in such agents. Furthermore, we evaluate our theoretical analysis with three sets of simulation-based experiments. The results demonstrate the feasibility of addictive wireheading in RL agents, and provide promising venues of further research on the psychopathological modeling of complex AI safety problems.

Research question: How can concepts and diagnostic criteria from psychology and psychiatry be applied to identify, characterize, and mitigate addictive or compulsive behaviors in reinforcement learning agents?
A joint measurement is presented of the branching fractions $B^0_s\toμ^+μ^-$ and $B^0\toμ^+μ^-$ in proton-proton collisions at the LHC by the CMS and LHCb experiments. The data samples were collected in 2011 at a centre-of-mass energy of 7 TeV, and in 2012 at 8 TeV. The combined analysis produces the first observation of the $B^0_s\toμ^+μ^-$ decay, with a statistical significance exceeding six standard deviations, and the best measurement of its branching fraction so far. Furthermore, evidence for the $B^0\toμ^+μ^-$ decay is obtained with a statistical significance of three standard deviations. The branching fraction measurements are statistically compatible with SM predictions and impose stringent constraints on several theories beyond the SM.

Research question: How do precise measurements of rare B meson decays to muon pairs constrain or rule out extensions to the Standard Model?
In risk management it is desirable to grasp the essential statistical features of a time series representing a risk factor. This tutorial aims to introduce a number of different stochastic processes that can help in grasping the essential features of risk factors describing different asset classes or behaviors. This paper does not aim at being exhaustive, but gives examples and a feeling for practically implementable models allowing for stylised features in the data. The reader may also use these models as building blocks to build more complex models, although for a number of risk management applications the models developed here suffice for the first step in the quantitative analysis. The broad qualitative features addressed here are {fat tails} and {mean reversion}. We give some orientation on the initial choice of a suitable stochastic process and then explain how the process parameters can be estimated based on historical data. Once the process has been calibrated, typically through maximum likelihood estimation, one may simulate the risk factor and build future scenarios for the risky portfolio. On the terminal simulated distribution of the portfolio one may then single out several risk measures, although here we focus on the stochastic processes estimation preceding the simulation of the risk factors Finally, this first survey report focuses on single time series. Correlation or more generally dependence across risk factors, leading to multivariate processes modeling, will be addressed in future work.

Research question: What practical steps and diagnostics should I use to choose, estimate, and validate a single-variate stochastic process for a financial time series that exhibits both fat tails and mean-reversion?
A joint measurement is presented of the branching fractions $B^0_s\toμ^+μ^-$ and $B^0\toμ^+μ^-$ in proton-proton collisions at the LHC by the CMS and LHCb experiments. The data samples were collected in 2011 at a centre-of-mass energy of 7 TeV, and in 2012 at 8 TeV. The combined analysis produces the first observation of the $B^0_s\toμ^+μ^-$ decay, with a statistical significance exceeding six standard deviations, and the best measurement of its branching fraction so far. Furthermore, evidence for the $B^0\toμ^+μ^-$ decay is obtained with a statistical significance of three standard deviations. The branching fraction measurements are statistically compatible with SM predictions and impose stringent constraints on several theories beyond the SM.

Research question: How do precise measurements of the rare decays of neutral B mesons into muon pairs test the Standard Model and constrain possible new physics scenarios?
A joint measurement is presented of the branching fractions $B^0_s\toμ^+μ^-$ and $B^0\toμ^+μ^-$ in proton-proton collisions at the LHC by the CMS and LHCb experiments. The data samples were collected in 2011 at a centre-of-mass energy of 7 TeV, and in 2012 at 8 TeV. The combined analysis produces the first observation of the $B^0_s\toμ^+μ^-$ decay, with a statistical significance exceeding six standard deviations, and the best measurement of its branching fraction so far. Furthermore, evidence for the $B^0\toμ^+μ^-$ decay is obtained with a statistical significance of three standard deviations. The branching fraction measurements are statistically compatible with SM predictions and impose stringent constraints on several theories beyond the SM.

Research question: How do precise measurements of rare neutral B meson decays to muon pairs constrain theories beyond the Standard Model, and which classes of new-physics models are most strongly affected?
A joint measurement is presented of the branching fractions $B^0_s\toμ^+μ^-$ and $B^0\toμ^+μ^-$ in proton-proton collisions at the LHC by the CMS and LHCb experiments. The data samples were collected in 2011 at a centre-of-mass energy of 7 TeV, and in 2012 at 8 TeV. The combined analysis produces the first observation of the $B^0_s\toμ^+μ^-$ decay, with a statistical significance exceeding six standard deviations, and the best measurement of its branching fraction so far. Furthermore, evidence for the $B^0\toμ^+μ^-$ decay is obtained with a statistical significance of three standard deviations. The branching fraction measurements are statistically compatible with SM predictions and impose stringent constraints on several theories beyond the SM.

Research question: How do precise measurements of rare B meson decays into muon pairs constrain physics beyond the Standard Model, and which types of new-physics scenarios are most strongly affected by these constraints?