Miracle-dz/UniFAR-FTUs huggingface dataset:
The Dutch list of essential drugs for undergraduate medical education: A modified Delphi study

Prescribing errors among junior doctors are common in clinical practice because many lack prescribing competence after graduation. This is in part due to inadequate education in clinical pharmacology and therapeutics (CP&T) in the undergraduate medical curriculum. To support CP&T education, it is important to determine which drugs medical undergraduates should be able to prescribe safely and effectively without direct supervision by the time they graduate. Currently, there is no such list with broad‐based consensus. Therefore, the aim was to reach consensus on a list of essential drugs for undergraduate medical education in the Netherlands.
Outcome of selective root canal retreatment—A retrospective study

Abstract Aim Selective root canal retreatment is when the treatment is limited to root(s) with radiographic evidence of periapical pathosis. The goals of this retrospective study were as follows: (i) evaluate the clinical and radiographic (periapical radiographs [PR] or cone‐beam computerized tomographs [CBCT]) outcome of selective root canal retreatment after ≥12 months follow‐up; (ii) evaluate the periapical status of the unretreated roots; and (iii) assess tooth survival. Methodology A retrospective study (January 2018 to April 2021) was conducted to identify permanent multirooted teeth that underwent selective root canal retreatment. Clinical records, PR and CBCT were examined to ascertain variables of interest. Outcomes (per root and per tooth) were classified into ‘favourable’ or ‘unfavourable’ using well‐established clinical and radiographic healing criteria. Treatment outcomes for the whole tooth and per root were compared as well as bivariate associations between the treatment outcome of the retreated roots and the treatment‐related parameters (quality of root filling, sealer extrusion, iatrogenic mishaps and type of restoration) were analysed using Fisher's exact test (α = .05). Survival was recorded in months. Results A total of 75 teeth (195 roots) in 75 subjects were available for outcome analysis. The favourable outcome per tooth was 86.7%. At follow‐up, 92.6% of the retreated roots had a favourable outcome. From the unretreated roots, 3.5% showed radiographic signs of an emerging periapical lesion. No statistical difference was shown between the outcomes per root and per tooth between both groups. None of the treatment‐related parameters had a direct influence on the outcome of the retreated roots. The survival rate at 12–48 months after retreatment was 91.5%. Conclusions Selective root canal retreatment is associated with a favourable outcome in a majority of cases. Unretreated roots rarely developed radiographic signs of a new periapical lesion at follow‐up. Future high‐quality clinical trials with larger sample sizes and longer follow‐up periods are required to confirm these findings.
Acquired atrioesophageal fistula: Need it be lethal? Sizing up the problem, diagnostic modalities, and best management

An atrioesophageal fistula is a devastating complication of ablation for atrial fibrillation. For the surgeon facing this dreaded complication, it may be a ‘once in a lifetime’ case. This review aims to describe the clinical problem and evaluate the outcome of different surgical techniques to start guiding cardiothoracic surgeons toward those which offer the best chance of survival.
To twist or not to twist: From chromophore structure to dynamics inside engineered photoconvertible and photoswitchable fluorescent proteins

Green‐to‐red photoconvertible fluorescent proteins (FPs) are vital biomimetic tools for powerful techniques such as super‐resolution imaging. A unique Kaede‐type FP named the least evolved ancestor (LEA) enables delineation of the evolutionary step to acquire photoconversion capability from the ancestral green fluorescent protein (GFP). A key residue, Ala69, was identified through several steady‐state and time‐resolved spectroscopic techniques that allows LEA to effectively photoswitch and enhance the green‐to‐red photoconversion. However, the inner workings of this functional protein have remained elusive due to practical challenges of capturing the photoexcited chromophore motions in real time. Here, we implemented femtosecond stimulated Raman spectroscopy and transient absorption on LEA‐A69T, aided by relevant crystal structures and control FPs, revealing that Thr69 promotes a stronger π–π stacking interaction between the chromophore phenolate (P‐)ring and His193 in FP mutants that cannot photoconvert or photoswitch. Characteristic time constants of ~60–67 ps are attributed to P‐ring twist as the onset for photoswitching in LEA (major) and LEA‐A69T (minor) with photoconversion capability, different from ~16/29 ps in correlation with the Gln62/His62 side‐chain twist in ALL‐GFP/ALL‐Q62H, indicative of the light‐induced conformational relaxation preferences in various local environments. A minor subpopulation of LEA‐A69T capable of positive photoswitching was revealed by time‐resolved electronic spectroscopies with targeted light irradiation wavelengths. The unveiled chromophore structure and dynamics inside engineered FPs in an aqueous buffer solution can be generalized to improve other green‐to‐red photoconvertible FPs from the bottom up for deeper biophysics with molecular biology insights and powerful bioimaging advances.
The effect of photoionizing feedback on star formation in isolated and colliding clouds

We investigate star formation occurring in idealised giant molecular clouds, comparing structures that evolve in isolation versus those undergoing a collision. Two different collision speeds are investigated and the impact of photoionising radiation from the stars is determined. We find that a colliding system leads to more massive star formation both with and without the addition of feedback, raising overall star formation efficiencies (SFE) by a factor of 10 and steepening the high-mass end of the stellar mass function. This rise in SFE is due to increased turbulent compression during the cloud collision. While feedback can both promote and hinder star formation in the isolated system, it increases the SFE by approximately 1.5 times in the colliding case when the thermal speed of the resulting HII regions matches the shock propagation speed in the collision.
Adaptive Landweber method to deblur images

We present an adaptive Landweber method (ALM) to reconstruct an image from a blurred observation. The standard Landweber method (LM) is an iterative method to solve "ill-posed" problems encountered in image restoration. The standard LM uses a constant update parameter. It has the disadvantage of slow convergence. Instead of using a constant update parameter, the adaptive method computes the update parameter at each iteration. In the ALM, the adaptive update parameter is calculated as the ratio of the L/sub 2/ norm of the first-order derivatives of the restored images at current and previous iterations. The adaptive LM emphasizes speed at the beginning stages and stability at late stages of iteration. The ALM has a higher convergence rate and lower MSE and mean absolute error than the standard LM. We use examples to demonstrate the performance of the ALM.
Aerobic exercise training selectively improves cortical inhibitory function after stroke

Background: Aerobic exercise elicits striking effects on neuroplasticity and cognitive executive function but is poorly understood after stroke. Objective: We tested the effect of 4 weeks of aerobic exercise training on inhibitory and facilitatory elements of cognitive executive function and electroencephalography (EEG) markers of cortical inhibition and facilitation. We investigated relationships between stimulus-evoked cortical responses, blood lactate levels during training, and aerobic fitness post-intervention. Methods: Twelve individuals with chronic (>6mo) stroke completed an intensive aerobic exercise intervention (40-mins, 3x/week). Electroencephalography and motor response times were assessed during congruent (response facilitation) and incongruent (response inhibition) stimuli of a Flanker task. Aerobic fitness capacity was assessed as VO2-peak during a treadmill test pre- and post-intervention. Blood lactate was assessed acutely (<1 min) after exercise each week. Cortical inhibition (N2) and facilitation (frontal P3) were quantified as peak amplitudes and latencies of stimulus evoked EEG activity over the frontal cortical region. Results: Following exercise training, the response inhibition speed increased while response facilitation remained unchanged. A relationship between earlier cortical N2 response and faster response inhibition emerged post-intervention. Individuals who produced higher lactate during exercise training achieved faster response inhibition and tended to show earlier cortical N2 responses post-intervention. There were no associations between VO2-peak and metrics of behavioral or neurophysiologic function. Conclusions: These findings provide novel evidence for selective benefits of aerobic exercise on inhibitory control during the initial 4-week period after initiation of exercise training, and implicate a potential therapeutic effect of lactate on post-stroke cortical inhibitory function.
SYMMETRIES AND THE TOPOLOGY OF DYNAMICAL SYSTEMS WITH TWO DEGREES OF FREEDOM

The problem of geodesic curves on a closed two-dimensional surface and some of its generalizations related with the addition of gyroscopic forces are considered. The authors study one-parameter groups of symmetries in the four-dimensional phase space that are generated by vector fields commuting with the original Hamiltonian vector field. If the genus of the surface is greater than one, then there are no nontrivial symmetries. For a surface of genus one (a two-dimensional torus) it is established that if there is an additional integral polynomial in the velocities, even or odd with respect to each component of the velocity, then there is a polynomial integral of degree one or two. For a surface of genus zero examples of nontrivial integrals of degree three and four are given. Fields of symmetries of first and second degree are studied. The presence of such symmetries is related to the existence of ignorable cyclic coordinates and separated variables. The influence of gyroscopic forces on the existence of fields of symmetries with polynomial components is studied.Bibliography: 9 titles.
Entanglement and conservation of orbital angular momentum in spontaneous parametric down-conversion

We show that the transfer of the plane-wave spectrum of the pump beam to the fourth-order transverse spatial correlation function of the two-photon field generated by spontaneous parametric down-conversion leads to the conservation and entanglement of orbital angular momentum of light. By means of a simple experimental setup based on fourth-order (or two-photon) interferometry, we show that our theoretical model provides a good description for down-converted fields carrying orbital angular momentum.
Attractive or repulsive nature of the Casimir force for rectangular cavity

The Casimir effect giving rise to an attractive or repulsive force between the configuration boundaries that confine the massless scalar field is reexamined for a (D{minus}1)-dimensional rectangular cavity with unequal finite p edges and different spacetime dimensions D in this paper. With periodic or Neumann boundary conditions, the energy is always negative. The case of Dirichlet boundary conditions is more complicated. The sign of the Casimir energy satisfying Dirichlet conditions on the surface of a hypercube (a cavity with equal finite p edges) depends on whether p is even or odd. In the general case (a cavity with unequal p edges), however, we show that the sign of the Casimir energy does not only depend on whether p is odd or even. Furthermore, we find that the Casimir force is always attractive if the edges are chosen appropriately. It is interesting that the Casimir force may be repulsive for odd p cavity with unequal edges, in contrast with the same problem in a hypercube case. {copyright} {ital 1997} {ital The American Physical Society}
Coupled Cluster Theory: Toward an Algebraic Geometry Formulation

Coupled cluster theory produced arguably the most widely used high-accuracy computational quantum chemistry methods. Despite the approach's overall great computational success, its mathematical understanding is so far limited to results within the realm of functional analysis. The coupled cluster amplitudes, which are the targeted objects in coupled cluster theory, correspond to solutions to the coupled cluster equations, which is a system of polynomial equations of at most degree four. The high dimensionality of the electronic Schr\"odinger equation and the non-linearity of the coupled cluster ansatz have so far stalled a formal analysis of this polynomial system. In this article, we present algebraic investigations that shed light on the coupled cluster equations and the root structure of this ansatz. This is of importance for the a posteriori evaluation of coupled cluster calculations. To that end, we investigate the root structure by means of Newton polytopes. We derive a general v-description, which is subsequently turned into an h-description for explicit examples. This perspective reveals an apparent connection between Pauli's exclusion principle and the geometrical structure of the Newton polytopes. We also propose an alternative characterization of the coupled cluster equations projected onto singles and doubles as cubic polynomials on an algebraic variety with certain sparsity patterns. Moreover, we provide numerical simulations of two computationally tractable systems, namely, the two electrons in four spin-orbitals system and the three electrons in six spin-orbitals system. These simulations provide novel insight into the root structure of the coupled cluster solutions when the coupled cluster ansatz is truncated.
Spin-dependent coupling of supercurrent and nonequilibrium quasiparticles in high-field superconductors

We report on an experimental investigation of the combined effect of nonequilibrium quasiparticle injection and supercurrent in superconducting aluminum wires. At low temperature, we observe the supercurrent-induced coupling of energy and charge imbalance with spectral resolution. At high magnetic fields, in the presence of a Zeeman splitting of the density of states, we find evidence for an additional spin-dependent coupling which has been recently predicted theoretically.
Do graph neural networks learn traditional jet substructure?

At the CERN LHC, the task of jet tagging, whose goal is to infer the origin of a jet given a set of final-state particles, is dominated by machine learning methods. Graph neural networks have been used to address this task by treating jets as point clouds with underlying, learnable, edge connections between the particles inside. We explore the decision-making process for one such state-of-the-art network, ParticleNet, by looking for relevant edge connections identified using the layerwise-relevance propagation technique. As the model is trained, we observe changes in the distribution of relevant edges connecting different intermediate clusters of particles, known as subjets. The resulting distribution of subjet connections is different for signal jets originating from top quarks, whose subjets typically correspond to its three decay products, and background jets originating from lighter quarks and gluons. This behavior indicates that the model is using traditional jet substructure observables, such as the number of prongs -- energetic particle clusters -- within a jet, when identifying jets.
Band structure in

We have investigated the structure of the collective bands in within our deformed configuration mixing (DCM) shell model based on Hartree - Fock states. In our model, the single particle orbits , , and are taken as the configuration space with as the core. A modified Kuo interaction for this basis space is used in our calculation. The different levels are classified into collective bands on the basis of the B(E2) values among them. The calculated collective bands and the B(E2) values are compared with available experimental data. Our calculation is able to reproduce the identical bands observed in , and .
Contrastive Credibility Propagation for Reliable Semi-Supervised Learning

Producing labels for unlabeled data is error-prone, making semi-supervised learning (SSL) troublesome. Often, little is known about when and why an algorithm fails to outperform a supervised baseline. Using benchmark datasets, we craft five common real-world SSL data scenarios: few-label, open-set, noisy-label, and class distribution imbalance/misalignment in the labeled and unlabeled sets. We propose a novel algorithm called Contrastive Credibility Propagation (CCP) for deep SSL via iterative transductive pseudo-label refinement. CCP unifies semi-supervised learning and noisy label learning for the goal of reliably outperforming a supervised baseline in any data scenario. Compared to prior methods which focus on a subset of scenarios, CCP uniquely outperforms the supervised baseline in all scenarios, supporting practitioners when the qualities of labeled or unlabeled data are unknown.
Layer-Stack Temperature Scaling

Recent works demonstrate that early layers in a neural network contain useful information for prediction. Inspired by this, we show that extending temperature scaling across all layers improves both calibration and accuracy. We call this procedure"layer-stack temperature scaling"(LATES). Informally, LATES grants each layer a weighted vote during inference. We evaluate it on five popular convolutional neural network architectures both in- and out-of-distribution and observe a consistent improvement over temperature scaling in terms of accuracy, calibration, and AUC. All conclusions are supported by comprehensive statistical analyses. Since LATES neither retrains the architecture nor introduces many more parameters, its advantages can be reaped without requiring additional data beyond what is used in temperature scaling. Finally, we show that combining LATES with Monte Carlo Dropout matches state-of-the-art results on CIFAR10/100.
Towards Fast Single-Trial Online ERP based Brain-Computer Interface using dry EEG electrodes and neural networks: a pilot study

Speeding up the spelling in event-related potentials (ERP) based Brain-Computer Interfaces (BCI) requires eliciting strong brain responses in a short span of time, as much as the accurate classification of such evoked potentials remains challenging and imposes hard constraints for signal processing and machine learning techniques. Recent advances in stimulus presentation and deep learning showcased a promising direction in significantly improving the efficacy of those systems, in this study we propose the combination of colored inverted face stimulation with classification using convolutional neural networks in the hard settings of dry electrodes and fast flashing single-trial ERP-based BCI. The high online accuracy achieved, with two subjects passing the 90 percent correct symbol detection bar and a transfer rate above 60 bits per minute, demonstrates the approach potential in improving the practicality of ERP based BCIs.
Exploring WavLM on Speech Enhancement

There is a surge in interest in self-supervised learning approaches for end-to-end speech encoding in recent years as they have achieved great success. Especially, WavLM showed state-of-the-art performance on various speech processing tasks. To better understand the efficacy of self-supervised learning models for speech enhancement, in this work, we design and conduct a series of experiments with three resource conditions by combining WavLM and two high-quality speech enhancement systems. Also, We propose a regression-based WavLM training objective and a noise-mixing data configuration to further boost the downstream enhancement performance. The experiments on the DNS challenge dataset and a simulation dataset show that the WavLM benefits the speech enhancement task in terms of both speech quality and speech recognition accuracy, especially for low fine-tuning resources. For the high fine-tuning resource condition, only the word error rate is substantially improved.
Short-range order and compositional phase stability in refractory high-entropy alloys via first-principles theory and atomistic modeling: NbMoTa, NbMoTaW, and VNbMoTaW

Using an all-electron, first principles, Landau-type theory, we study the nature of short-range order and compositional phase stability in equiatomic refractory high entropy alloys, NbMoTa, NbMoTaW, and VNbMoTaW. We also investigate selected binary subsystems to provide insight into the physical mechanisms driving order. Our approach examines the short-range order of the solid solutions directly, infers disorder/order transitions, and also extracts parameters suitable for atomistic modelling of diffusional phase transformations. We find a hierarchy of relationships between the chemical species in these materials which promote ordering tendencies. The most dominant is a relative atomic size difference between the 3d element, V, and the other 4d and 5d elements which drives a B32-like order. For systems where V is not present, ordering is dominated by the difference in filling of valence states; pairs of elements which are isoelectronic remain weakly correlated to low temperatures, while pairs with a valence difference present B2-like order. Our estimated order-disorder transition temperature in VNbMoTaW is sufficiently high for us to suggest that SRO in this material may be experimentally observable.
Effects of Active Galactic Nucleus Feedback on Cold Gas Depletion and Quenching of Central Galaxies

We investigate the influence of active galactic nucleus (AGN) feedback on the galaxy cold gas content and its connection to galaxy quenching in three hydrodynamical simulations of Illustris, IllustrisTNG, and SIMBA. By comparing to the observed atomic and molecular neutral hydrogen measurements for central galaxies, we find that Illustris overpredicts the cold gas masses in star-forming galaxies and significantly underpredicts them for quenched galaxies. IllustrisTNG performs better in this comparison than Illustris, but quenched galaxies retain too much cold gas compared with observations. SIMBA shows good agreement with observations, by depleting the global cold gas reservoir for quenched galaxies. We find that the discrepancies in IllustrisTNG are caused by its weak kinetic AGN feedback that only redistributes the cold gas from the inner disks to the outer regions and reduces the inner cold gas densities. It agrees with observations much better when only the cold gas within the stellar disk is considered to infer the star formation rates. From dependences of the cold gas reservoir on the black hole mass and Eddington ratio, we find that the cumulative energy release during the black hole growth is the dominant reason for the cold gas depletion and thus the galaxy quenching. We further measure the central stellar surface density within 1 kpc (Σ1) for the high-resolution run of IllustrisTNG and find a tight correlation between Σ1 and black hole mass. It suggests that the observed decreasing trend of cold gas mass with Σ1 is also a reflection of the black hole growth.