Miracle-dz/UniFAR-FTUs huggingface dataset:
GRAPPA-GANs for Parallel MRI Reconstruction

k-space undersampling is a standard technique to accelerate MR image acquisitions. Reconstruction techniques including GeneRalized Autocalibrating Partial Parallel Acquisition(GRAPPA) and its variants are utilized extensively in clinical and research settings. A reconstruction model combining GRAPPA with a conditional generative adversarial network (GAN) was developed and tested on multi-coil human brain images from the fastMRI dataset. For various acceleration rates, GAN and GRAPPA reconstructions were compared in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). For an acceleration rate of R=4, PSNR improved from 33.88 using regularized GRAPPA to 37.65 using GAN. GAN consistently outperformed GRAPPA for various acceleration rates.
A generalized powers averaging property for commutative crossed products

We prove a generalized version of Powers' averaging property that characterizes simplicity of reduced crossed products $C(X) \rtimes_\lambda G$, where $G$ is a countable discrete group, and $X$ is a compact Hausdorff space which $G$ acts on minimally by homeomorphisms. As a consequence, we generalize results of Hartman and Kalantar on unique stationarity to the state space of $C(X) \rtimes_\lambda G$ and to Kawabe's generalized space of amenable subgroups $\operatorname{Sub}_a(X,G)$. This further lets us generalize a result of the first named author and Kalantar on simplicity of intermediate C*-algebras. We prove that if $C(Y) \subseteq C(X)$ is an inclusion of unital commutative $G$-C*-algebras with $X$ minimal and $C(Y) \rtimes_\lambda G$ simple, then any intermediate C*-algebra $A$ satisfying $C(Y) \rtimes_\lambda G \subseteq A \subseteq C(X) \rtimes_\lambda G$ is simple.
X-ray and ultraviolet observations of the eclipsing cataclysmic variables OV Bootis and SDSS J103533.02+055158.3 with degenerate donors

Context.The majority of cataclysmic variables are predicted to be post-period minimum systems with degenerate donor stars, the period bouncers. Owing to their intrinsic faintness, however, only a handful of these systems have so far been securely identified.Aims. We want to study the X-ray properties of two eclipsing period bouncers, OV Bootis and SDSS J103533.02+055158.3, that were selected for this study due to their proximity to Earth.Methods. We have obtainedXMM-Newtonphase-resolved X-ray and ultraviolet observations of the two objects for spectral and timing analysis.Results. Owing to a recent dwarf nova outburst OV Bootis was much brighter than SDSS J103533.02+055158.3 at X-ray and ultraviolet wavelengths and the eclipse could be studied in some detail. An updated eclipse ephemeris was derived. The X-rays were shown to originate close to the white dwarf, the boundary layer, with significant absorption affecting its spectrum. There was no absorption in SDSS J103533.02+055158.3, despite being observed at the same inclination indicating different shapes of the disk and the disk rim. The white-dwarf temperature was re-determined for both objects: the white dwarf in OV Bootis was still hot (23 000 K) five months after a dwarf nova outburst, and the white dwarf in SDSS J103533.02+055158.3 hotter than assumed previously (Teff = 11 500 K). Conclusions.All three cataclysmic variables with degenerate donors studied so far in X-rays, including SDSS J121209.31+013627.7, were clearly discovered in X-rays and revealed mass accretion ratesṀ= 8 × 10−15− 4 × 10 − 13M⊙yr−1. If their X-ray behavior is representative of the subpopulation of period bouncers, the all-sky X-ray surveys with eROSITA together with comprehensive follow-up will uncover new objects in sufficient number to address the remaining questions concerning late-stage cataclysmic variable evolution.
Collective variables for the study of crystallisation

ABSTRACT The phenomenon of solidification of a substance from its liquid phase is of the greatest practical and theoretical importance, and atomistic simulations can provide precious information towards its understanding and control. Unfortunately, the time scale for crystallisation is much larger than what can be explored in standard simulations. Enhanced sampling methods can overcome this time scale hurdle. Many such methods rely on the definition of appropriate collective variables able to capture the slow degrees of freedom. To this effect, we introduce collective coordinates of general applicability to crystallisation simulations. They are based on the peaks of the three-dimensional structure factor that are combined non-linearly via the Deep Linear Discriminant Analysis machine learning method. We use these collective variables in the context of the on-the-fly probability enhanced sampling method that is a recent evolution of metadynamics. We demonstrate the validity of this approach by studying the crystallisation of a multicomponent system, Sodium Chloride, and a molecular system, Carbon Dioxide. GRAPHICAL ABSTRACT
Contextual Classification Using Self-Supervised Auxiliary Models for Deep Neural Networks

Classification problems solved with deep neural networks (DNNs) typically rely on a closed world paradigm, and optimize over a single objective (e.g., minimization of the cross-entropy loss). This setup dismisses all kinds of supporting signals that can be used to reinforce the existence or absence of particular patterns. The increasing need for models that are interpretable by design makes the inclusion of said contextual signals a crucial necessity. To this end, we introduce the notion of Self-Supervised Autogenous Learning (SSAL). A SSAL objective is realized through one or more additional targets that are derived from the original supervised classification task, following architectural principles found in multi-task learning. SSAL branches impose low-level priors into the optimization process (e.g., grouping). The ability of using SSAL branches during inference, allow models to converge faster, focusing on a richer set of class-relevant features. We equip state-of-the-art DNNs with SSAL objectives and report consistent improvements for all of them on CIFAR100 and Imagenet. We show that SSAL models outperform similar state-of-the-art methods focused on contextual loss functions, auxiliary branches and hierarchical priors.
When does the Physarum Solver Distinguish the Shortest Path from other Paths: the Transition Point and its Applications

Physarum solver, also called the physarum polycephalum inspired algorithm (PPA), is a newly developed bio-inspired algorithm that has an inherent ability to find the shortest path in a given graph. Recent research has proposed methods to develop this algorithm further by accelerating the original PPA (OPPA)'s path-finding process. However, when does the PPA ascertain that the shortest path has been found? Is there a point after which the PPA could distinguish the shortest path from other paths? By innovatively proposing the concept of the dominant path (D-Path), the exact moment, named the transition point (T-Point), when the PPA finds the shortest path can be identified. Based on the D-Path and T-Point, a newly accelerated PPA named OPPA-D using the proposed termination criterion is developed which is superior to all other baseline algorithms according to the experiments conducted in this paper. The validity and the superiority of the proposed termination criterion is also demonstrated. Furthermore, an evaluation method is proposed to provide new insights for the comparison of different accelerated OPPAs. The breakthrough of this paper lies in using D-path and T-point to terminate the OPPA. The novel termination criterion reveals the actual performance of this OPPA. This OPPA is the fastest algorithm, outperforming some so-called accelerated OPPAs. Furthermore, we explain why some existing works inappropriately claim to be accelerated algorithms is in fact a product of inappropriate termination criterion, thus giving rise to the illusion that the method is accelerated.
Learning Low-Correlation GPS Spreading Codes with a Policy Gradient Algorithm

With the birth of the next-generation GPS III constellation and the upcoming launch of the Navigation Technology Satellite-3 (NTS-3) testing platform to explore future technologies for GPS, we are indeed entering a new era of satellite navigation. Correspondingly, it is time to revisit the design methods of the GPS spreading code families. In this work, we develop a Gaussian policy gradient-based reinforcement learning algorithm which constructs high-quality families of spreading code sequences. We demonstrate the ability of our algorithm to achieve better mean-squared auto-and cross-correlation than well-chosen families of equal-length Gold codes and Weil codes. Furthermore, we compare our algorithm with an analogous genetic algorithm implementation assigned the same code evaluation metric. To the best of the authors’ knowledge, this is the ﬁrst work to explore using a machine learning / reinforcement learning approach to design navigation spreading codes
Stable recovery of a metric tensor from the partial hyperbolic Dirichlet to Neumann map

In this paper we consider the inverse problem of determining on a compact Riemannian manifold the metric tensor in the wave equation with Dirichlet data from measured Neumann boundary observations. This information is enclosed in the dynamical Dirichlet-to-Neumann map associated to the wave equation. We prove in dimension n ě 2 that the knowledge of the Dirichlet-to-Neumann map for the wave equation uniquely determines the metric tensor and we establish logarithm-type stability.
A computational study on the hydrogenation of CO2 catalyzed by a tetraphos-ligated cobalt complex: monohydride vs. dihydride

Density functional theory (DFT) calculations were used to study the mechanisms of hydrogenation of carbon dioxide catalyzed by the tetraphos-ligated (PP3: P(CH2CH2PPh2)3) cobalt complexes. We investigated the binding modes between CO2 and the cobalt metal center to determine whether the CO2 coordinated to the metal center in the catalytic processes. The monohydride catalytic pathway (Path I) and the dihydride catalytic pathway (Path II) for the hydrogenation of CO2 have been explored. In these two cases, a weak H⋯CO2 interaction leads to cleavage of the Co–H bond and subsequent formation of the formate ligand. Moreover, the transformation from the dihydride to the monohydride is endergonic by 9.2 kcal mol−1 and the relevant free energy barrier is about 20.9 kcal mol−1. However, the largest free energy barrier of 19.1 kcal mol−1 in Path II is significantly lower than that in Path I (22.8 kcal mol−1), which corresponds to the hydride transfer from the cobalt center to CO2. The detailed comparisons of the possible pathways suggest that Path II is much more favoured than Path I and that it is not necessary to form the monohydride species in the whole catalytic cycle. Our results, which unambiguously demonstrate that the active catalyst is the dihydride rather than the monohydride, are consistent with the experimental observations and, most importantly, provide detailed mechanistic insight.
Electron Ptychography. II. Theory of Three-Dimensional Propagation Effects

The interpretation of image reconstructions obtained by ptychography in a scanning transmission electron microscope (STEM) is investigated. In this technique, a number of coherent electron diffraction patterns are obtained from adjacent points of a crystalline sample by scanning a focused electron beam. The phase problem is solved by using an interference phenomenon, thus obtaining a very high resolution (0.136 nm) reconstruction of the specimen. Simulations presented here assist experiments described in a previous paper [Nellist & Rodenburg (1998). Acta Cryst. A54, 49–60]. In this paper, the simulation method which is best suited for the calculation of ptychographical reconstructions for perfect crystals is described. Simulation results are presented for the simplest case of diffraction beams with single overlap and it is shown that the reconstruction does not match the exit-surface wave function for axial plane-wave illumination but instead resembles the image wave function with a fixed focus setting on the middle section of the specimen. A second reconstruction method is described, in which a greater angular diameter of the aperture is used and every beam is re-interfered with the central beam. The variation of the amplitude and phase of all reconstructed beams with crystal thickness is very similar up to a thickness of about 25 nm. It is argued that such a simple relationship can only be expected for projected structures containing identical atomic columns.
Nano-BF3.SiO2: A reusable and eco-friendly catalyst for thioacetalization and trans-thioacetalization reactions

Nano-silica supported boron trifluoride (BF3.SiO2) is an efficient, reusable and eco-friendly catalyst for chemoselective thioacetalization of aldehydes and ketones. So, this catalyst was applied for transthioacetalization of acetals and acylals into their corresponding 1,3-dithiolanes or 1,3-dithianes in good to excellent yields. The reactions were carried out at room temperature under solvent free and grinding conditions in 1.5-2.5 minutes.
Method for reduced SAR T1ρ‐weighted MRI

A reduced specific absorption rate (SAR) version of the T1ρ‐weighted MR pulse sequence was designed and implemented. The reduced SAR method employs a partial k‐space acquisition approach in which a full power spin‐lock pulse is applied to only the central phase‐encode lines of k‐space, while the remainder of k‐space receives a low‐power spin‐lock pulse. Acquisition of high‐ and low‐power phase‐encode lines are interspersed chronologically to minimize average power deposition. In this way, the majority of signal energy in the central portion of k‐space receives full T1ρ‐weighting, while the average SAR of the overall acquisition can be reduced, thereby lowering the minimum safely allowable TR. The pulse sequence was used to create T1ρ maps of a phantom, an in vivo mouse brain, and the brain of a human volunteer. In the images of the human brain, SAR was reduced by 40% while the measurements of T1ρ differed by only 2%. The reduced SAR sequence enables T1ρ‐weighted MRI in a clinical setting, even at high field strengths. Magn Reson Med 51:1096–1102, 2004. © 2004 Wiley‐Liss, Inc.
Molecular modelling and NMR studies of the caffeine dimer

A survey of crystal structures containing the xanthine ring shows that caffeine-like molecules tend to stack in parallel in a variety of stacking geometries, suggesting that a stacked pair of caffeine molecules has many conformations of comparable energy. Molecular modelling suggests that the caffeine dimer, the major associated species in aqueous solution, may occur in nine distinct conformations. In agreement with the crystal survey and the modelling results, NMR spectra of caffeine solutions exhibit intermolecular nuclear Overhauser enhancements (NOEs), consistent with a dynamic equilibrium of several conformations of the dimer of comparable energies.Key words: caffeine, dimer, self-association, molecular modelling, intermolecular nuclear Overhauser enhancements (NOEs).
R‐RAFT approach for the polymerization of N‐isopropylacrylamide with a star poly(ε‐caprolactone) core

Reversible addition-fragmentation chain transfer (RAFT) polymerization is a more robust and versatile approach than other living free radical polymerization methods, providing a reactive thiocarbonylthio end group. A series of well-defined star diblock [poly(e-caprolactone)-b-poly(N-isopropylacrylamide)]4 (SPCLNIP) copolymers were synthesized by R-RAFT polymerization of N-isopropylacrylamide (NIPAAm) using [PCL-DDAT]4 (SPCL-DDAT) as a star macro-RAFT agent (DDAT: S-1-dodecyl-S′-(α, α′-dimethyl-α″-acetic acid) trithiocarbonate). The R-RAFT polymerization showed a controlled/“living” character, proceeding with pseudo-first-order kinetics. All these star polymers with different molecular weights exhibited narrow molecular weight distributions of less than 1.2. The effect of polymerization temperature and molecular weight of the star macro-RAFT agent on the polymerization kinetics of NIPAAm monomers was also addressed. Hardly any radical–radical coupling by-products were detected, while linear side products were kept to a minimum by careful control over polymerization conditions. The trithiocarbonate groups were transferred to polymer chain ends by R-RAFT polymerization, providing potential possibility of further modification by thiocarbonylthio chemistry. © 2011 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2011
Variation of the r.f. response of a Langmuir probe with amplitude and frequency

The r.f. response of a double Langmuir probe immersed in a laboratory plasma has been measured over a wide range of signal amplitude, signal frequency and plasma electron density. A theory is developed which predicts (in direct contradiction to the theory of other workers) a decrease in the probe sheath capacitance with increasing frequency in the neighbourhood of the ion plasma frequency, and a probe response above this frequency which at high amplitudes obeys a current is proportional to (voltage)¼ dependence. While no significant change of capacity with frequency is observed, possibly owing to experimental limitations, the high-amplitude results are in good agreement with theory and do show the appropriate current is proportional to (voltage)¼ dependence. This is in contrast to earlier step waveform (i.e. low-frequency) measurements which showed a current is proportional to (voltage)¾ dependence.
In Vivo Optical Metabolic Imaging of Long-Chain Fatty Acid Uptake in Orthotopic Models of Triple-Negative Breast Cancer

Simple Summary A dysregulated metabolism is a hallmark of cancer. Once understood, tumor metabolic reprogramming can lead to targetable vulnerabilities, spurring the development of novel treatment strategies. Beyond the common observation that tumors rely heavily on glucose, building evidence indicates that a subset of tumors use lipids to maintain their proliferative or metastatic phenotype. This study developed an intra-vital microscopy method to quantify lipid uptake in breast cancer murine models using a fluorescently labeled palmitate molecule, Bodipy FL c16. This work highlights optical imaging’s ability to both measure metabolic endpoints non-destructively and repeatedly, as well as inform small animal metabolic phenotyping beyond in vivo optical imaging of breast cancer alone. Abstract Targeting a tumor’s metabolic dependencies is a clinically actionable therapeutic approach; however, identifying subtypes of tumors likely to respond remains difficult. The use of lipids as a nutrient source is of particular importance, especially in breast cancer. Imaging techniques offer the opportunity to quantify nutrient use in preclinical tumor models to guide development of new drugs that restrict uptake or utilization of these nutrients. We describe a fast and dynamic approach to image fatty acid uptake in vivo and demonstrate its relevance to study both tumor metabolic reprogramming directly, as well as the effectiveness of drugs targeting lipid metabolism. Specifically, we developed a quantitative optical approach to spatially and longitudinally map the kinetics of long-chain fatty acid uptake in in vivo murine models of breast cancer using a fluorescently labeled palmitate molecule, Bodipy FL c16. We chose intra-vital microscopy of mammary tumor windows to validate our approach in two orthotopic breast cancer models: a MYC-overexpressing, transgenic, triple-negative breast cancer (TNBC) model and a murine model of the 4T1 family. Following injection, Bodipy FL c16 fluorescence increased and reached its maximum after approximately 30 min, with the signal remaining stable during the 30–80 min post-injection period. We used the fluorescence at 60 min (Bodipy60), the mid-point in the plateau region, as a summary parameter to quantify Bodipy FL c16 fluorescence in subsequent experiments. Using our imaging platform, we observed a two- to four-fold decrease in fatty acid uptake in response to the downregulation of the MYC oncogene, consistent with findings from in vitro metabolic assays. In contrast, our imaging studies report an increase in fatty acid uptake with tumor aggressiveness (6NR, 4T07, and 4T1), and uptake was significantly decreased after treatment with a fatty acid transport inhibitor, perphenazine, in both normal mammary pads and in the most aggressive 4T1 tumor model. Our approach fills an important gap between in vitro assays providing rich metabolic information at static time points and imaging approaches visualizing metabolism in whole organs at a reduced resolution.
Dynamic Changes of Generic Quality of Life after Different Treatments for Localized Prostate Cancer

Generic quality of life (QoL) is an important issue in decision making related to the primary treatment of localized prostate cancer (PC). This study assessed the dynamic changes of QoL in patients with localized PC under different treatment modalities. From 2013 to 2018, we prospectively assessed QoL scores in patients with localized PC under unitary treatment using the World Health Organization Quality of Life (WHOQOL) BREF version. The trajectories of the QoL scores after different treatments were estimated using a kernel-smoothing method. Dynamic changes in the major determinants were analyzed using a mixed effects model. The clinical features of the participants in our institute were compared with PC patients in Taiwan’s cancer registry. A total of 196 patients were enrolled with 491 repeated assessments. The participants shared similar clinical characteristics with the PC patients in Taiwan as a whole. Patients with lower household incomes showed statistically significant lower scores on all four domains and related facets, while PC survivors with comorbidities of anxiety and/or diabetes appeared to be affected on the physical domain and related facets. After controlling for these determinants, patients under active surveillance or observation demonstrated significantly higher QoL scores in the physical and social domains, as well as several facets belonging to these domains, in mixed models compared with patients undergoing radical prostatectomy or radiotherapy within the first year. The generic QoL scores were higher within the first year in patients receiving active surveillance or observation after controlling other significant factors. The difference diminished after one year of post management. More studies are needed to corroborate our findings.