dyfan/halluhard-seed-questions huggingface dataset:
We discuss the role of water bridging the DNA-enzyme interaction by resorting to recent results showing that London dispersion forces between delocalized electrons of base pairs of DNA are responsible for the formation of dipole modes that can be recognized by \textit{Taq} polymerase. We describe the dynamic origin of the high efficiency and precise targeting of \textit{Taq} activity in PCR. The spatiotemporal distribution of interaction couplings, frequencies, amplitudes, and phase modulations comprise a pattern of fields which constitutes the electromagnetic image of DNA in the surrounding water, which is what the polymerase enzyme actually recognizes in the DNA water environment. The experimental realization of PCR amplification, achieved through replacement of the DNA template by the treatment of pure water with electromagnetic signals recorded from viral and bacterial DNA solutions, is found consistent with the gauge theory paradigm of quantum fields.

Research question: How could structured or polarized water transmit or store electromagnetic patterns produced by biomolecules so that other biomolecules could recognize those patterns, and what physical mechanisms and experimental evidence support this idea?
Background: Spinal cord injury triggers complex pathological cascades, resulting in destructive tissue damage and incomplete tissue repair. Scar formation is generally considered as a barrier for regeneration in central nervous system (CNS), while the intrinsic mechanism of scar-forming after spinal cord injury has not been completed deciphered. Methods: We assessed cholesterol hemostasis in spinal cord lesions and injured peripheral nerves using confocal reflection microscopy and real-time PCR analyses. The involvement of the proteins, which were predicted to promote cholesterol efflux in spinal cord lesions, were assessed with Liver X receptor (LXR) agonist and Apolipoprotein E (APOE) deficiency. The role of reverse cholesterol transport (RCT) in cholesterol clearance was examined in APOE KO mice injured sciatic nerves and myelin-overloaded macrophages in vitro. Finally, we determined the consequence of excess cholesterol accumulation in CNS by transplantation of myelin into neonatal spinal cord lesions. Results: We found that excess cholesterol accumulates in phagocytes and is inefficiently removed in spinal cord lesions in young-adult mice. Interestingly, we observed that excessive cholesterol also accumulates in injured peripheral nerves, but is subsequently removed by RCT. Meanwhile, preventing RCT led to macrophage accumulation and fibrosis in injured peripheral nerves. Furthermore, the neonatal mouse spinal cord lesions are devoid of myelin-derived lipids, and able to heal without excess cholesterol accumulation. We found that transplantation of myelin into neonatal lesions disrupts healing with excessive cholesterol accumulation, persistent macrophage activation and fibrosis, indicating myelin-derived cholesterol plays a critical role in impaired wound healing.

Research question: How does cholesterol accumulation within phagocytes affect inflammation and scar formation after nervous system injury, and what strategies could be used to promote cholesterol clearance to improve healing?
This study examined the relationship between trade facilitation and economic growth among the middle-income countries from 2010 to 2020 using 94 countries made up of 48 lower-middle-income countries and 46 upper-middle-income countries. The study utilized both difference and system Generalised Method of Moments (GMM) since the cross-sections (N) were greater than the periods (T). The study found that container port traffic, quality of trade and transport-related infrastructure have a strong influence on imports and exports of goods and national income while trade tariff hurts the growth of the countries. The study also found that most of the trade facilitation indicators indicated a weak positive influence on trade flows and economic growth. Based on these findings, the study recommends that reforms aimed at significantly lowering the costs of trading across borders among middle-income countries should be highly prioritized in policy formulations, with a focus on the export side by reducing at-the-border documentation, time, and real costs of trading across borders while the international organizations should continue to report the set of Trade Facilitation Indicators (TFIs) that identify areas for action and enable the potential impact of reforms to be assessed.

Research question: What practical policy measures can middle-income countries implement to reduce at-the-border trade costs and improve their export competitiveness?
Here, we report the synthesis of hard carbon materials(CSH) made from corn starch and their application as an anode in lithium-ion batteries. The study shows that the Microstructure and electrochemical properties of CSHs are affected by nitrogen doping. It is found that nitrogen is embedded in the carbon layer with graphite nitrogen, pyridine nitrogen, and pyrrole nitrogen, so as to the surface morphology was changed and reduced the disorder of the materials. The electrochemical test results show that the introduction of nitrogen elements can increase the reversible capacity of the material, with the first discharge capacity reaching above 426.35 mAh g-1, and the rate performance also improves. When triethylenetetramine and pre-carbonized corn starch are carbonized at a mass ratio of 1:9, the obtained material has a reversible capacity of 122.04 mAh g-1 at a rate of 2 C. During the carbonization process, the nitrogen in triethylenetetramine is doped into the carbon materials, improving the electrochemical performance of the material. Keywords: Lithium-ion battery; Hard carbon; Corn starch; Nitrogen doping;

Research question: How does nitrogen doping alter the structure and lithium-storage mechanisms of biomass-derived hard carbon anodes, and why does that typically improve their capacity and rate performance?
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 branching fractions for rare neutral B meson decays to muon pairs test the Standard Model and constrain theories beyond it?
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 scenarios 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 to muon pairs constrain extensions of the Standard Model, and which classes of new-physics models are most tightly constrained by these results?
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 advantages and potential challenges of studying muonic hydrogen atoms and their reactions in vacuum compared with using bulk gas, liquid, or solid targets?
Sewage sludge, a biosolid product of wastewater processing, is an often-overlooked source of rich organic waste. Hydrothermal processing (HTP), which uses heat and pressure to convert biomass into various solid, liquid, and gaseous products, has shown promise in converting sewage sludge into new materials with potential application in biofuels, asphalt binders, and bioplastics. In this study we focus on hydrochar, the carbonaceous HTP solid phase, and investigate its use as a bio-based filler in additive manufacturing technologies. We explore the impact of HTP and subsequent thermal activation on chemical and structural properties of sewage sludge and discuss the role of atypical metallic and metalloid dopants in organic material processing. In additive manufacturing composites, although the addition of hydrochar generally decreases mechanical performance, we show that toughness and strain can be recovered with hierarchical microstructures, much like biological materials that achieve outstanding properties by architecting relatively weak building blocks.

Research question: How can hierarchical microstructures be designed or implemented in composite materials to recover toughness and ductility when relatively weak bio-based fillers (like hydrochar) are used in additive manufacturing?
In the present study, we have described how by using molecular docking and molecular dynamic (MD) simulation studies the combination drug of ivermectin and doxycycline can be used as a potential inhibitor for SARS-CoV-2 virus. In lieu of unavailability of specific cure of COVID-19 till now various possibilities for individual and combination drugs have been explored by the medical practitioners/scientists for the remedial purpose of CoV-2 infections. $3CL^{pro}$ is the main protease of SARS-CoV-2 virus which plays an essential role in mediating viral replication in the human body. $3CL^{pro}$ protein can serve as an attractive drug target. In this work, we have studied drug: $3CL^{pro}$ interactions by in silico molecular docking and MD simulation approaches. Common and easily available antiviral drugs ivermectin, doxycycline and their combination have been proved their valid candidature to be used as potential drug candidates against SARS-CoV-2 infections.

Research question: What experimental and clinical steps are required to validate a candidate drug or drug combination that is predicted to inhibit a viral protease before it can be recommended for patient treatment?
The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors has brought on new opportunities for applying both Deep and Spiking Neural Network (SNN) algorithms to healthcare and biomedical applications at the edge. This can facilitate the advancement of medical Internet of Things (IoT) systems and Point of Care (PoC) devices. In this paper, we provide a tutorial describing how various technologies including emerging memristive devices, Field Programmable Gate Arrays (FPGAs), and Complementary Metal Oxide Semiconductor (CMOS) can be used to develop efficient DL accelerators to solve a wide variety of diagnostic, pattern recognition, and signal processing problems in healthcare. Furthermore, we explore how spiking neuromorphic processors can complement their DL counterparts for processing biomedical signals. The tutorial is augmented with case studies of the vast literature on neural network and neuromorphic hardware as applied to the healthcare domain. We benchmark various hardware platforms by performing a sensor fusion signal processing task combining electromyography (EMG) signals with computer vision. Comparisons are made between dedicated neuromorphic processors and embedded AI accelerators in terms of inference latency and energy. Finally, we provide our analysis of the field and share a perspective on the advantages, disadvantages, challenges, and opportunities that various accelerators and neuromorphic processors introduce to healthcare and biomedical domains.

Research question: What are the main trade-offs (in terms of energy efficiency, latency, robustness, and ease of development) when choosing between neuromorphic processors and conventional deep-learning accelerators for real-time biomedical signal processing at the edge?
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 branching fractions for rare decays like B_s→μ+μ− and B^0→μ+μ− constrain physics beyond the Standard Model, and which types of new-physics scenarios are most strongly affected?
Solar radio type II bursts serve as early indicators of incoming geo-effective space weather events such as coronal mass ejections (CMEs). In order to investigate the origin of high-frequency type II bursts (HF type II bursts), we have identified 51 of them (among 180 type II bursts from SWPC reports) that are observed by ground-based Compound Astronomical Low-cost Low-frequency Instrument for Spectroscopy and Transportable Observatory (CALLISTO) spectrometers and whose upper-frequency cutoff (of either fundamental or harmonic emission) lies in between 150 MHz-450 MHz during 2010-2019. We found that 60% of HF type II bursts, whose upper-frequency cutoff $\geq$ 300 MHz originate from the western longitudes. Further, our study finds a good correlation $\sim $ 0.73 between the average shock speed derived from the radio dynamic spectra and the corresponding speed from CME data. Also, we found that analyzed HF type II bursts are associated with wide and fast CMEs located near the solar disk. In addition, we have analyzed the spatio-temporal characteristics of two of these high-frequency type II bursts and compared the derived from radio observations with those derived from multi-spacecraft CME observations from SOHO/LASCO and STEREO coronagraphs.

Research question: What physical mechanisms generate high-frequency solar type II radio bursts, and how do the observed burst frequencies inform us about the height, speed, and properties of the associated coronal shocks and CMEs?
Waste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, either for economic or ecological reasons, and the industry demands high efficiency. Our team conducted comprehensive research on Artificial Intelligence usage in waste detection and classification to fight the world's waste pollution problem. As a result an open-source framework that enables the detection and classification of litter was developed. The final pipeline consists of two neural networks: one that detects litter and a second responsible for litter classification. Waste is classified into seven categories: bio, glass, metal and plastic, non-recyclable, other, paper and unknown. Our approach achieves up to 70% of average precision in waste detection and around 75% of classification accuracy on the test dataset. The code used in the studies is publicly available online.

Research question: What are the main challenges and practical considerations when deploying AI-based systems for detecting and classifying litter in real-world outdoor environments, and how can their accuracy and robustness be improved?
Renal Cell Carcinoma is typically asymptomatic at the early stages for many patients. This leads to a late diagnosis of the tumor, where the curability likelihood is lower, and makes the mortality rate of Renal Cell Carcinoma high, with respect to its incidence rate. To increase the survival chance, a fast and correct categorization of the tumor subtype is paramount. Nowadays, computerized methods, based on artificial intelligence, represent an interesting opportunity to improve the productivity and the objectivity of the microscopy-based Renal Cell Carcinoma diagnosis. Nonetheless, much of their exploitation is hampered by the paucity of annotated dataset, essential for a proficient training of supervised machine learning technologies. This study sets out to investigate a novel self supervised training strategy for machine learning diagnostic tools, based on the multi-resolution nature of the histological samples. We aim at reducing the need of annotated dataset, without significantly reducing the accuracy of the tool. We demonstrate the classification capability of our tool on a whole slide imaging dataset for Renal Cancer subtyping, and we compare our solution with several state-of-the-art classification counterparts.

Research question: How can self-supervised learning leverage multi-resolution histopathology images to reduce the need for annotated data while still maintaining diagnostic accuracy for tumor subtype classification?
POLAR is a dedicated Gamma-Ray Burst polarimeter making use of Compton-scattering which took data from the second Chinese spacelab, the Tiangong-2 from September 2016 to April 2017. It has a wide Field of View of $\sim6$ steradians and an effective area of $\sim400\ cm^2$ at 300 keV. These features make it one of the most sensitive instruments in its energy range (15-500 keV), and therefore capable of almost continuously monitoring persistent sources such as pulsars. Significant folded pulsation from both PSR B0531+21 (the Crab Pulsar) and PSR B1509-58 has been observed. Observations of the Crab Pulsar with POLAR have previously been used for phase-resolved spectroscopy of the Crab Pulsar to calibrate the instrumental responses of POLAR. In this work, we investigate a polarimetric joint-fitting method for observations of the Crab Pulsar with POLAR. Unlike a GRB observation with POLAR, the observations of the Crab Pulsar are complicated by multiple observational datasets during which the polarization plane rotates as well. So before fitting, we have to correct the modulation curves under different datasets, by taking into account the rotations of the Crab Pulsar's relative position in the detctor's local coordinate, and the changes of detector response in different datasets. Despite these difficulties and the low signal to background for such sources constraining, polarization measurements were possible with the POLAR data. We will present the methodology briefly, which could be applied to any wide FoV polarimeter, and polarization results of the Crab pulsar with POLAR. Finally, the inferred ability of pulsar detection with POLAR-2 (the successor of POLAR) will also be discussed.

Research question: What are the main challenges in performing phase-resolved hard X-ray/gamma-ray polarimetry of pulsars with wide-field Compton-scattering polarimeters, and what general techniques are used to correct for detector rotation and time-varying instrument response?
Eccentric planets may spend a significant portion of their orbits at large distances from their host stars, where low temperatures can cause atmospheric CO2 to condense out onto the surface, similar to the polar ice caps on Mars. The radiative effects on the climates of these planets throughout their orbits would depend on the wavelength-dependent albedo of surface CO2 ice that may accumulate at or near apoastron and vary according to the spectral energy distribution of the host star. To explore these possible effects, we incorporated a CO2 ice-albedo parameterization into a one-dimensional energy balance climate model. With the inclusion of this parameterization, our simulations demonstrated that F-dwarf planets require 29% more orbit-averaged flux to thaw out of global water ice cover compared with simulations that solely use a traditional pure water ice-albedo parameterization. When no eccentricity is assumed, and host stars are varied, F-dwarf planets with higher bond albedos relative to their M-dwarf planet counterparts require 30% more orbit-averaged flux to exit a water snowball state. Additionally, the intense heat experienced at periastron aids eccentric planets in exiting a snowball state with a smaller increase in instellation compared with planets on circular orbits; this enables eccentric planets to exhibit warmer conditions along a broad range of instellation. This study emphasizes the significance of incorporating an albedo parameterization for the formation of CO2 ice into climate models to accurately assess the habitability of eccentric planets, as we show that, even at moderate eccentricities, planets with Earth-like atmospheres can reach surface temperatures cold enough for the condensation of CO2 onto their surfaces, as can planets receiving low amounts of instellation on circular orbits.

Research question: How does the spectral type of a host star influence the radiative impact of surface CO2 ice on an exoplanet’s climate and habitability?