dyfan/halluhard-seed-questions huggingface dataset:
The various decay mechanisms of excitons in cuprous oxide (Cu2O) are highly sensitive to defects which can relax selection rules. Here we report cryogenic hyperspectral imaging of exciton luminescence from cuprous oxide crystals grown via the floating zone method showing the samples have few defects. Some locations, however, show strain splitting of the 1s orthoexciton triplet polariton luminescence. Strain is reduced by annealing. In addition, annealing causes annihilation of oxygen and copper vacancies, which leads to a negative correlation between luminescence of unlike vacancies.

Research question: How do crystal defects (e.g., vacancies) and strain influence exciton decay pathways and luminescence in semiconductors, and in what ways can annealing modify these defects to restore or change excitonic optical properties?
The Lustre parallel file system has been widely adopted by high-performance computing (HPC) centers as an effective system for managing large-scale storage resources. Lustre achieves unprecedented aggregate performance by parallelizing I/O over file system clients and storage targets at extreme scales. Today, 7 out of 10 fastest supercomputers in the world use Lustre for high-performance storage. To date, Lustre development has focused on improving the performance and scalability of large-scale scientific workloads. In particular, large-scale checkpoint storage and retrieval, which is characterized by bursty I/O from coordinated parallel clients, has been the primary driver of Lustre development over the last decade. With the advent of extreme scale computing and Big Data computing, many HPC centers are seeing increased user interest in running diverse workloads that place new demands on Lustre. In March 2015, the International Workshop on the Lustre Ecosystem: Challenges and Opportunities was held in Annapolis, Maryland at the Historic Inns of Annapolis Governor Calvert House. This workshop series is intended to help explore improvements in the performance and flexibility of Lustre for supporting diverse application workloads. The 2015 workshop was the inaugural edition, and the goal was to initiate a discussion on the open challenges associated with enhancing Lustre for diverse applications, the technological advances necessary, and the associated impacts to the Lustre ecosystem. The workshop program featured a day of tutorials and a day of technical paper presentations.

Research question: What are the main challenges in adapting a large-scale parallel file system to efficiently support both traditional bursty HPC checkpointing workloads and modern diverse Big Data analytics workloads?
To investigate the effect of wettability on multiphase flow in porous media, hydrophilic glass surfaces are typically modified through a silanization process. This study examines the nanoscale chemical and structural modifications of glass bead surfaces treated with Surfasil, using inverse gas chromatography and atomic force microscopy. The results show that silanization reduces both specific and dispersive components of surface energy, indicating fewer polar groups and lower total energy, leading to decreased hydrophilicity compared to untreated glass beads. BET surface area measurements and AFM images reveal that the surface becomes progressively smoother with increased silanization.
  Subsequently, this study assessed the stability and extent of surface modifications in silanized samples caused by adsorbed water during storage, using untreated glass beads as a reference. Untreated samples exhibit increases in surface roughness and polar groups, leading to marginal increase in surface energy and hydrophilicity. In contrast, the silanized samples show resistance to water adsorption, with only minor alterations in surface energy and structure, likely occurring in areas where the silanization coating was incomplete. The results suggest that humidity control is crucial during extended storage, as prolonged moisture exposure could still lead to surface modifications, even in silanized samples, potentially affecting wettability consistency in repeated experiments.

Research question: How does long-term exposure to humidity or adsorbed water change the wettability and surface chemistry of silanized glass surfaces, and what storage conditions best preserve their hydrophobicity?
This white paper describes the LSST Dark Energy Science Collaboration (DESC), whose goal is the study of dark energy and related topics in fundamental physics with data from the Large Synoptic Survey Telescope (LSST). It provides an overview of dark energy science and describes the current and anticipated state of the field. It makes the case for the DESC by laying out a robust analytical framework for dark energy science that has been defined by its members and the comprehensive three-year work plan they have developed for implementing that framework. The analysis working groups cover five key probes of dark energy: weak lensing, large scale structure, galaxy clusters, Type Ia supernovae, and strong lensing. The computing working groups span cosmological simulations, galaxy catalogs, photon simulations and a systematic software and computational framework for LSST dark energy data analysis. The technical working groups make the connection between dark energy science and the LSST system. The working groups have close linkages, especially through the use of the photon simulations to study the impact of instrument design and survey strategy on analysis methodology and cosmological parameter estimation. The white paper describes several high priority tasks identified by each of the 16 working groups. Over the next three years these tasks will help prepare for LSST analysis, make synergistic connections with ongoing cosmological surveys and provide the dark energy community with state of the art analysis tools. Members of the community are invited to join the LSST DESC, according to the membership policies described in the white paper. Applications to sign up for associate membership may be made by submitting the Web form at http://www.slac.stanford.edu/exp/lsst/desc/signup.html with a short statement of the work they wish to pursue that is relevant to the LSST DESC.

Research question: How do the main cosmological probes—weak gravitational lensing, large-scale structure, galaxy clusters, Type Ia supernovae, and strong lensing—complement one another in constraining dark energy, and what are the primary systematic uncertainties unique to each probe?
We propose a systematic approach to obtain various forms of insulating titanium oxynitrides Ti$_{n}$N$_{2}$O$_{2n-3}$ and we conduct a detailed study on its $n=2$ case, Ti$_{2}$N$_{2}$O. We study the energetics and the electronic structures of Ti$_{2}$N$_{2}$O and compare these results with those of pristine and nitrogen-doped TiO$_{2}$ within the framework of the density-functional theory (DFT) and the GW approximation. We find that Ti$_{2}$N$_{2}$O is semiconducting with the calculated band-gap of 1.81 eV, which is significantly smaller than those of pristine TiO$_{2}$ rutile (3.14 eV) or anatase (3.55 eV). Furthermore, the reduction of the band-gap of Ti$_{2}$N$_{2}$O is realized not by lowering of the conduction-band minimum but by rising the valence-band maximum. Therefore the proposed Ti$_{2}$N$_{2}$O has suitable band-edge alignment for water-splitting photocatalysis. Finally, total energy calculations indicate that Ti$_{2}$N$_{2}$O is potentially easier to synthesize than nitrogen-doped TiO$_{2}$. Based on these results, we propose Ti$_{2}$N$_{2}$O as a promising visible-light photocatalytic material.

Research question: How does shifting the valence-band maximum upward (instead of lowering the conduction-band minimum) affect a semiconductor’s suitability and efficiency for visible-light-driven water-splitting photocatalysis?
Assessments of impacts of climate change and future projections over the Indian region, have so far relied on a single regional climate model (RCM) - eg., the PRECIS RCM of the Hadley Centre, UK. While these assessments have provided inputs to various reports (e.g., INCCA 2010; NATCOMM2 2012), it is important to have an ensemble of climate projections drawn from multiple RCMs due to large uncertainties in regional-scale climate projections. Ensembles of multi-RCM projections driven under different perceivable socio-economic scenarios are required to capture the probable path of growth, and provide the behavior of future climate and impacts on various biophysical systems and economic sectors dependent on such systems.
  The Centre for Climate Change Research, Indian Institute of Tropical Meteorology (CCCR-IITM) has generated an ensemble of high resolution downscaled projections of regional climate and monsoon over South Asia until 2100 for the Intergovernmental Panel for Climate Change (IPCC)using a RCM (ICTP-RegCM4) at 50 km horizontal resolution, by driving the regional model with lateral and lower boundary conditions from multiple global atmosphere-ocean coupled models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The future projections are based on three Representation Concentration Pathway (RCP) scenarios (viz., RCP2.6, RCP4.5, RCP8.5) of the IPCC.

Research question: How do ensembles of regional climate model simulations reduce uncertainty in regional climate projections compared with relying on a single regional model, and what are the main remaining sources of uncertainty?
Beamforming is central to the processing function of all phased arrays and becomes particularly challenging with a large number of antenna element (e.g. >100,000). The ability to beamform efficiently with reasonable power requirements is discussed in this paper. Whilst the most appropriate beamforming technology will change over time due to semiconductor and processing developments, we present a hierarchical structure which is technology agnostic and describe both Radio-Frequency (RF) and digital hierarchical beamforming approaches. We present implementations of both RF and digital beamforming systems on two antenna array demonstrators, namely the Electronic Multi Beam Radio Astronomy ConcEpt (EMBRACE) and the dualpolarisation all-digital array (2-PAD). This paper will compare and contrast both digital and analogue implementations without considering the deep system design of these arrays.

Research question: What are the main practical trade-offs between analogue (RF) and digital hierarchical beamforming approaches for very large phased arrays in terms of power consumption, scalability, and beamforming flexibility?
Automated segmentation of kidneys and kidney tumors is an important step in quantifying the tumor's morphometrical details to monitor the progression of the disease and accurately compare decisions regarding the kidney tumor treatment. Manual delineation techniques are often tedious, error-prone and require expert knowledge for creating unambiguous representation of kidneys and kidney tumors segmentation. In this work, we propose an end-to-end boundary aware fully Convolutional Neural Networks (CNNs) for reliable kidney and kidney tumor semantic segmentation from arterial phase abdominal 3D CT scans. We propose a segmentation network consisting of an encoder-decoder architecture that specifically accounts for organ and tumor edge information by devising a dedicated boundary branch supervised by edge-aware loss terms. We have evaluated our model on 2019 MICCAI KiTS Kidney Tumor Segmentation Challenge dataset and our method has achieved dice scores of 0.9742 and 0.8103 for kidney and tumor repetitively and an overall composite dice score of 0.8923.

Research question: What are the main challenges to deploying automated kidney and kidney tumor segmentation tools in routine clinical practice, and how can these tools be validated to ensure reliability across different scanners and patient populations?
This review explores the synthesis, characterization, and therapeutic applications of zinc oxide nanoparticles (ZnO NPs) in the treatment of diabetes mellitus. The study delves into both chemical and green synthesis methods, comparing their impacts on nanoparticle properties. Key characterization techniques such as XRD, FTIR, UV-Vis spectroscopy, and SEM confirm the crystalline structure, optical properties, and morphology of the nanoparticles. ZnO NPs demonstrate significant biological activities, including antibacterial, anti-inflammatory, and antidiabetic effects. These nanoparticles show promise in improving glucose regulation, enhancing insulin sensitivity, and boosting glucose uptake in cells. Despite these benefits, the potential toxicity and long-term effects of ZnO NPs warrant further investigation. Future research should focus on optimizing synthesis methods and conducting comprehensive studies to fully exploit ZnO NPs' potential in diabetes management and other biomedical applications.

Research question: What are the known mechanisms of toxicity for zinc oxide nanoparticles in the body, and what strategies are used to reduce their potential harmful effects for safe therapeutic use?
In the rapidly expanding field of two-dimensional materials, magnetic monolayers show great promise for the future applications in nanoelectronics, data storage, and sensing. The research in intrinsically magnetic two-dimensional materials mainly focuses on synthetic iodide and telluride based compounds, which inherently suffer from the lack of ambient stability. So far, naturally occurring layered magnetic materials have been vastly overlooked. These minerals offer a unique opportunity to explore air-stable complex layered systems with high concentration of local moment bearing ions. We demonstrate magnetic ordering in iron-rich two-dimensional phyllosilicates, focusing on mineral species of minnesotaite, annite, and biotite. These are naturally occurring van der Waals magnetic materials which integrate local moment baring ions of iron via magnesium/aluminium substitution in their octahedral sites. Due to self-inherent capping by silicate/aluminate tetrahedral groups, ultra-thin layers are air-stable. Chemical characterization, quantitative elemental analysis, and iron oxidation states were determined via Raman spectroscopy, wavelength disperse X-ray spectroscopy, X-ray absorption spectroscopy, and X-ray photoelectron spectroscopy. Superconducting quantum interference device magnetometry measurements were performed to examine the magnetic ordering. These layered materials exhibit paramagnetic or superparamagnetic characteristics at room temperature. At low temperature ferrimagnetic or antiferromagnetic ordering occurs, with the critical ordering temperature of 38.7 K for minnesotaite, 36.1 K for annite, and 4.9 K for biotite. In-field magnetic force microscopy on iron bearing phyllosilicates confirmed the paramagnetic response at room temperature, present down to monolayers.

Research question: What structural or chemical features make naturally occurring layered minerals more air-stable than many synthetic two-dimensional magnetic compounds, and how do those features help preserve magnetic properties when the materials are thinned to monolayers?
Decoding the genome confers the capability to predict characteristics of the organism(phenotype) from DNA (genotype). We describe the present status and future prospects of genomic prediction of complex traits in humans. Some highly heritable complex phenotypes such as height and other quantitative traits can already be predicted with reasonable accuracy from DNA alone. For many diseases, including important common conditions such as coronary artery disease, breast cancer, type I and II diabetes, individuals with outlier polygenic scores (e.g., top few percent) have been shown to have 5 or even 10 times higher risk than average. Several psychiatric conditions such as schizophrenia and autism also fall into this category. We discuss related topics such as the genetic architecture of complex traits, sibling validation of polygenic scores, and applications to adult health, in vitro fertilization (embryo selection), and genetic engineering.

Research question: How accurate and clinically useful are polygenic risk scores for predicting an individual’s risk of common diseases, and what are the main factors that limit their predictive power?
The recent explosion of false claims in social media and on the Web in general has given rise to a lot of manual fact-checking initiatives. Unfortunately, the number of claims that need to be fact-checked is several orders of magnitude larger than what humans can handle manually. Thus, there has been a lot of research aiming at automating the process. Interestingly, previous work has largely ignored the growing number of claims about images. This is despite the fact that visual imagery is more influential than text and naturally appears alongside fake news. Here we aim at bridging this gap. In particular, we create a new dataset for this problem, and we explore a variety of features modeling the claim, the image, and the relationship between the claim and the image. The evaluation results show sizable improvements over the baseline. We release our dataset, hoping to enable further research on fact-checking claims about images.

Research question: What are the key challenges and approaches for automatically verifying whether a textual claim is supported, contradicted, or unrelated to a given image?
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 theories beyond the Standard Model, and which types of new physics models are most strongly impacted by such measurements?
High-precision 3D printing technology opens to almost endless opportunities to design complex shapes present in tailored architected materials. The scope of this work is to review the latest studies regarding 3D printed lattice structures that involve the use of photopolymers fabricated by Material Jetting (MJ), with a focus on the widely used Polyjet and MultiJet techniques. The main aspects governing this printing process are introduced to determine their influence during the fabrication of 3D printed lattices. Performed experimental studies, considered assumptions, and constitutive models for the respective numerical simulations are analyzed. Furthermore, an overview of the latest extensively studied 3D printed architected lattice materials is exposed by emphasizing their achieved mechanical performances through the use of Ashby plots. Then, we highlight the advantages, limitations, and challenges of the material jetting technology to manufacture tunable architected materials for innovative devices, oriented to several engineering applications. Finally, possible approaches for future works and gaps to be covered by further research are indicated, including cost and environmental-related issues.

Research question: What are the main factors that determine the mechanical performance and manufacturability of high-precision photopolymer 3D-printed lattice structures, and how can designers balance resolution, material properties, and printing constraints when optimizing for stiffness, strength, or energy absorption?
This chapter focuses on vibration energy harvesting using electrostatic converters. It synthesizes the various works carried out on electrostatic devices, from concepts, models and up to prototypes, and covers both standard (electret-free) and electret-based electrostatic vibration energy harvesters (VEH).

Research question: What are the main advantages and disadvantages of electret-based versus electret-free electrostatic vibration energy harvesters for practical, long-term deployment?
Studies of muonic hydrogen atoms and molecules have been performed traditionally in bulk targets of gas, liquid or solid. At TRIUMF, Canada's meson facility, we have developed a new type of target system using multilayer thin films of solid hydrogen, which provides a beam of muonic hydrogen atoms in vacuum. Using the time-of-flight of the muonic atoms, the energy-dependent information of muonic reactions are obtained in direct manner. We discuss some unique measurements enabled by the new technique, with emphasis on processes relevant to muon catalyzed fusion.

Research question: What are the main advantages and technical challenges of producing and studying muonic hydrogen atoms in vacuum using thin solid hydrogen layers compared with traditional bulk gas, liquid, or solid targets?
Wikipedia and many User-Generated Content (UGC) communities are known for producing reliable, quality content, but also for being vulnerable to false or misleading information. Previous work has shown that many hoaxes on Wikipedia go undetected for extended periods of time. But little is known about the creation of intentionally false or misleading information online. Does collective attention toward a topic increase the likelihood it will spawn disinformation? Here, we measure the relationship between allocation of attention and the production of hoax articles on the English Wikipedia. Analysis of traffic logs reveals that, compared to legitimate articles created on the same day, hoaxes tend to be more associated with traffic spikes preceding their creation. This is consistent with the idea that the supply of false or misleading information on a topic is driven by the attention it receives. These findings improve our comprehension of the determinants of disinformation in UGC communities and could help promote the integrity of knowledge on Wikipedia.

Research question: What mechanisms might explain why increased public attention to a topic makes it more likely that false or misleading content will be created about it?
Statistics has moved beyond the frequentist-Bayesian controversies of the past. Where does this leave our ability to interpret results? I suggest that a philosophy compatible with statistical practice, labeled here statistical pragmatism, serves as a foundation for inference. Statistical pragmatism is inclusive and emphasizes the assumptions that connect statistical models with observed data. I argue that introductory courses often mischaracterize the process of statistical inference and I propose an alternative "big picture" depiction.

Research question: How can introductory statistics courses be redesigned to emphasize the role of model assumptions and pragmatic interpretation of results while still teaching core techniques?