Miracle-dz/UniFAR-FTUs huggingface dataset:
Regional redistribution of CB1 cannabinoid receptors in human foetal brains with Down's syndrome and their functional modifications in Ts65Dn+/+ mice

The endocannabinoid system with its type 1 cannabinoid receptor (CB1R) expressed in postmitotic neuroblasts is a critical chemotropic guidance module with its actions cascading across neurogenic commitment, neuronal polarisation and synaptogenesis in vertebrates. Here, we present the systematic analysis of regional CB1R expression in the developing human brain from gestational week 14 until birth. In parallel, we diagrammed differences in CB1R development in Down syndrome foetuses and identified altered CB1R signalling.
Motivations for Seeking Cosmetic Enhancing Procedures of the Face: A Systematic Review

Supplemental Digital Content is Available in the Text. BACKGROUND Cosmetic enhancing procedures continue to grow in demand. Physicians should understand the complex factors that drive patient motivation for seeking such procedures. OBJECTIVE In contrast to a lens of psychopathology, this review reveals the driving power of everyday intrapersonal, social, and behavioral factors that motivate interest in elective facial cosmetic procedures. MATERIALS AND METHODS The review was conducted according to PRISMA guidelines and included studies with at least 50 adult patients seeking facial cosmetic enhancements between January 1, 2000, and July 1, 2022. RESULTS Among 1,239 identified publications, 21 studies with 9,005 participants were selected for inclusion. The review documents everyday factors as patient motivators for pursuing cosmetic enhancements of the face, with the majority of work focusing on intrapersonal factors (17 of 21 studies), such as preventing aging or negative appearance based self-appraisals. For studies reporting social factors (15 of 21 studies), the most common motivators were the patient's social network and a desire to promote social standing. Behavioral factors revealed that social media and media consumption impact patient motivation for cosmetic enhancements (5 of 21 studies). CONCLUSION In summary, this review demonstrates that patient motivations for facial cosmetic enhancements may be best understood through everyday intrapersonal, social, and behavioral factors.
Determination of mean and deviatoric stresses in shock loaded solids

Models for the behavior of solids submitted to shock waves include an equation of state and a plastic yield surface, which represents the plastic potential. The general purpose of this work concerns various methods used to obtain these equations by means of the determination of the mean and deviatoric shock streeses. Emphasis is placed on the method of ’’piezoresistive deviatoric gauges’’ that we have been using since 1973. This method does not include any theoretical hypothesis, and is suitable for all materials that can be gauged. Examples of applications on polymethyl metacrylate, limestone, and steel are reported and show that the precision of the piezoresistive deviatoric gauges method depends upon the material, namely the deviator magnitude, and upon the stress range explored.
Health Status Outcomes in Older Adults Undergoing Chronic Total Occlusion Percutaneous Coronary Intervention

Background Although chronic total occlusions (CTOs) are common in older adults, they are less likely to be offered CTO percutaneous coronary intervention for angina relief than younger adults. The health status impact of CTO percutaneous coronary intervention in adults aged ≥75 years has not been studied. We sought to compare technical success rates and angina‐related health status outcomes at 12 months between adults aged ≥75 and <75 years in the OPEN‐CTO (Outcomes, Patient Health Status, and Efficiency in Chronic Total Occlusion) registry. Methods and Results Angina‐related health status was assessed with the Seattle Angina Questionnaire (score range 0–100, higher scores denote less angina). Technical success rates were compared using hierarchical modified Poisson regression, and 12‐month health status was compared using hierarchical multivariable linear regression between adults aged ≥75 and <75 years. Among 1000 participants, 19.8% were ≥75 years with a mean age of 79.5±4.1 years. Age ≥75 years was associated with a lower likelihood of technical success (adjusted risk ratio=0.92 [95% CI, 0.86–0.99; P=0.02]) and numerically higher rates of in‐hospital major adverse cardiovascular events (9.1% versus 5.9%, P=0.10). There was no difference in Seattle Angina Questionnaire Summary Score at 12 months between adults aged ≥75 and <75 years (adjusted difference=0.9 [95% CI, −1.4 to 3.1; P=0.44]). Conclusions Despite modestly lower success rates and higher complication rates, adults aged ≥75 years experienced angina‐related health status benefits after CTO‐percutaneous coronary intervention that were similar in magnitude to adults aged <75 years. CTO percutaneous coronary intervention should not be withheld based on age alone in otherwise appropriate candidates.
Comparison of biometry measurements and intraocular lens power prediction between 2 SS‐OCT–based biometers

The Eyestar 900 and IOLMaster 700 had strong agreement in biometry measurements and IOL power prediction by the Barrett Universal II formula using either standard or total corneal keratometry. Purpose: To evaluate the agreement in biometry measurements and intraocular lens (IOL) power prediction between the Eyestar 900 and the IOLMaster 700. Setting: Institutional. Design: Retrospective comparative study. Methods: Patients were evaluated before cataract surgery using both devices on the same visit. Axial length, anterior and posterior keratometry, anterior chamber depth, corneal diameter (CD), central corneal thickness, and lens thickness were recorded by both devices. The agreement in measurements and in IOL power calculations was evaluated using the Barrett Universal II (BU-II) formula with either predicted or measured posterior keratometry. Results: In total, 402 eyes of 402 consecutive patients were included. The mean age was 72.0 ± 9.2 years. Clinically, mean differences in measured variables were small, albeit slightly larger for posterior flat and steep keratometry (0.43 diopters [D] and 0.42 D, respectively). The measurement correlation and agreement between the devices were good for all variables with slightly lower agreement in CD measurements. Consistent bias was seen in measurements of posterior flat and steep keratometry. Good agreement was also found in anterior and posterior astigmatism measurements. Good IOL power calculation agreement was found using either predicted posterior keratometry (95% limits of agreement [LoA] of −0.40 to +0.30 D) or measured posterior keratometry (95% LoA of −0.45 to +0.40 D). The agreement was within ±0.5 D in 394 eyes (98.0%) using predicted posterior keratometry and in 386 eyes (96.0%) using measured posterior keratometry. Conclusions: The Eyestar 900 and the IOLMaster 700 show strong agreement in biometry measurements and IOL power prediction by the BU-II formula using either standard or total corneal keratometry and can be used interchangeably.
The Minimal Difference as an Individual Threshold to Examine the Utility of a Verification Bout in Determining V̇O2max

ABSTRACT Purpose A square-wave verification bout to confirm maximal oxygen uptake (V̇O2max) from a graded exercise test (GXT) has been recommended based on mean responses. This study used the test–retest reliability, mean, and individual differences between the highest V̇O2 from the GXT (V̇O2GXT) and verification bout (V̇O2verification) to examine the efficacy of a verification bout in the determination of V̇ O2max in healthy, recreationally trained, well-motivated men. Methods Ten men (24 ± 4 yr) completed a GXT on a cycle ergometer followed by a submaximal verification bout to determine V̇O2GXT and V̇O2verification. After completion of the initial GXT, subjects rested for 5 min then performed the verification bout at 90% of the peak power output from the initial GXT. Analyses included a two-way repeated-measures ANOVA, intraclass correlation coefficients (ICC2,1), standard errors of the measurement (SEM), minimal differences (MD), and coefficients of variation (COV). Results There was no test (test 1 vs test 2)–method (GXT vs verification) interaction (P = 0.300) and no main effect for test (P = 0.690), but there was a main effect for method (P = 0.003). The V̇O2GXT (46.0 mL⋅kg−1⋅min−1) was significantly greater than V̇O2verification (43.9 mL⋅kg−1⋅min−1), collapsed across test. The V̇O2GXT (ICC = 0.970, SEM = 1.63 mL⋅kg−1⋅min−1, MD = 4.51 mL⋅kg−1⋅min−1, COV = 3.54%) and the V̇O2verification (ICC = 0.953, SEM = 1.87 mL⋅kg−1⋅min−1, MD = 5.17 mL⋅kg−1⋅min−1, COV = 4.25%) demonstrated “excellent” reliability. No subject exceeded the MD test–retest for V̇O2GXT or V̇O2verification. No subject had a V̇O2verification that exceeded V̇O2GXT by more than the MD, but two subjects had a V̇O2GXT, which exceeded V̇O2verification by more than the MD. Conclusions The excellent reliability of V̇O2GXT in addition to the examination of the individual differences between V̇O2GXT and V̇O2verification using the MD indicated that a standalone GXT was sufficient to determine V̇O2max.
High-resolution infrared spectroscopy of R Aquarii

A time series of high-resolution 1.5-2.5 micron spectra of the symbiotic Mira variable R Aquarii has been observed over the last decade. As expected, the spectra reveal only lines originating the Mira. The photospheric spectrum of the Mira appears totally normal. Velocity, excitation temperature, and column density information are presented as a function of phase. The pulsation of the Mira observed in the infrared is very regular, allowing orbital velocity changes to be searched for at the few km/s level. The data show that, assuming a semiamplitude greater than about 1 km/s, the orbital period must be either between 18 and 21 yr or longer than 32 yr. The derived orbit is highly uncertain but the data are consistent with a rather elliptical orbit of long period. If the derived orbit is valid, the size of the Roche lobe surrounding the Mira becomes small enough at periastron to influence the atmosphere of the Mira. 48 refs.
Penicillin-Binding Proteins and Alternative Dual-Beta-Lactam Combinations for Serious Enterococcus faecalis Infections with Elevated Penicillin MICs

Ampicillin-ceftriaxone has become a first-line therapy for Enterococcus faecalis endocarditis. We characterized the penicillin-binding protein (PBP) profiles of various E. faecalis strains and tested for synergy to better inform beta-lactam options for the treatment of E. faecalis infections. ABSTRACT Ampicillin-ceftriaxone has become a first-line therapy for Enterococcus faecalis endocarditis. We characterized the penicillin-binding protein (PBP) profiles of various E. faecalis strains and tested for synergy to better inform beta-lactam options for the treatment of E. faecalis infections. We assessed the affinity of PBP2B from elevated-MIC strain E. faecalis LS4828 compared to type strain JH2-2 using the fluorescent beta-lactam Bocillin FL. We also characterized pbp4 and pbpA structures and PBP4 and PBP2B expression and used deletion and complementation studies to assess the impact of PBP2B on the levels of resistance. We tested penicillin-susceptible and -resistant E. faecalis isolates against ceftriaxone or ceftaroline combinations with other beta-lactams in 24-h time-kill studies. Two penicillin-susceptible strains (JH2-2 and L2052) had identical pbp sequences and similar PBP expression levels. One reduced-penicillin-susceptibility strain (L2068) had pbp sequences identical to those of the susceptible strains but expressed more PBP4. The second decreased-penicillin-susceptibility strain (LS4828) had amino acid substitutions in both PBP4 and PBP2B and expressed increased quantities of both proteins. PBP2B did not appear to contribute significantly to the elevated beta-lactam MICs. No synergy was demonstrable against the strains with both mutated PBPs and increased expression (L2068 and LS4828). Meropenem plus ceftriaxone or ertapenem plus ceftriaxone demonstrated the most consistent synergistic activity. PBP2B of strain LS4828 does not contribute significantly to reduced penicillin susceptibility. Neither the MIC nor the level of PBP expression correlated directly with the identified synergistic combinations when tested at static subinhibitory concentrations.
Rethinking Soft Label in Label Distribution Learning Perspective

The primary goal of training in early convolutional neural networks (CNN) is the higher generalization performance of the model. However, as the expected calibration error (ECE), which quantiﬁes the explanatory power of model inference, was recently introduced, research on training models that can be explained is in progress. We hypothesized that a gap in supervision criteria during training and inference leads to overconﬁdence, and investigated that performing label distribution learning (LDL) would enhance the model calibration in CNN training. To verify this assumption, we used a simple LDL setting with recent data augmentation techniques. Based on a series of experiments, the following results are obtained: 1) State-of-the-art KD methods signiﬁcantly impede model calibration. 2) Training using LDL with recent data augmentation can have excellent effects on model calibration and even in generalization performance. 3) Online LDL brings additional improvements in model calibration and accuracy with long training, especially in large-size models. Using the proposed approach, we simultaneously achieved a lower ECE and higher generalization performance for the image classiﬁcation datasets CIFAR10, 100, STL10, and ImageNet. We performed several visualiza-tions and analyses and witnessed several interesting behaviors in CNN training with the LDL.
Energy-Conserving Neural Network for Turbulence Closure Modeling

In turbulence modeling, we are concerned with finding closure models that represent the effect of the subgrid scales on the resolved scales. Recent approaches gravitate towards machine learning techniques to construct such models. However, the stability of machine-learned closure models and their abidance by physical structure (e.g. symmetries, conservation laws) are still open problems. To tackle both issues, we take the `discretize first, filter next' approach. In this approach we apply a spatial averaging filter to existing fine-grid discretizations. The main novelty is that we introduce an additional set of equations which dynamically model the energy of the subgrid scales. Having an estimate of the energy of the subgrid scales, we can use the concept of energy conservation to derive stability. The subgrid energy containing variables are determined via a data-driven technique. The closure model is used to model the interaction between the filtered quantities and the subgrid energy. Therefore the total energy should be conserved. Abiding by this conservation law yields guaranteed stability of the system. In this work, we propose a novel skew-symmetric convolutional neural network architecture that satisfies this law. The result is that stability is guaranteed, independent of the weights and biases of the network. Importantly, as our framework allows for energy exchange between resolved and subgrid scales it can model backscatter. To model dissipative systems (e.g. viscous flows), the framework is extended with a diffusive component. The introduced neural network architecture is constructed such that it also satisfies momentum conservation. We apply the new methodology to both the viscous Burgers' equation and the Korteweg-De Vries equation in 1D. The novel architecture displays superior stability properties when compared to a vanilla convolutional neural network.
A Catalog of 71 Coronal Line Galaxies in MaNGA: [Ne v] Is an Effective AGN Tracer

Despite the importance of active galactic nuclei (AGNs) in galaxy evolution, accurate AGN identification is often challenging, as common AGN diagnostics can be confused by contributions from star formation and other effects (e.g., Baldwin–Phillips–Terlevich diagrams). However, one promising avenue for identifying AGNs is “coronal emission lines” (“CLs”), which are highly ionized species of gas with ionization potentials ≥100 eV. These CLs may serve as excellent signatures for the strong ionizing continuum of AGNs. To determine if CLs are in fact strong AGN tracers, we assemble and analyze the largest catalog of optical CL galaxies using the Sloan Digital Sky Survey's Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) catalog. We detect CL emission in 71 MaNGA galaxies, out of the 10,010 unique galaxies from the final MaNGA catalog, with ≥5σ confidence. In our sample, we measure [Ne v]λ3347, λ3427, [Fe vii]λ3586, λ3760, λ6086, and [Fe x]λ6374 emission and crossmatch the CL galaxies with a catalog of AGNs that were confirmed with broad-line, X-ray, IR, and radio observations. We find that [Ne v] emission, compared to [Fe vii] and [Fe x] emission, is best at identifying high-luminosity AGNs. Moreover, we find that the CL galaxies with the least dust extinction yield the most iron CL detections. We posit that the bulk of the iron CLs are destroyed by dust grains in the galaxies with the highest [O iii] luminosities in our sample, and that AGNs in the galaxies with low [O iii] luminosities are possibly too weak to be detected using traditional techniques.
Towards learned emulation of interannual water isotopologue variations in General Circulation Models

Abstract Simulating abundances of stable water isotopologues, that is, molecules differing in their isotopic composition, within climate models allows for comparisons with proxy data and, thus, for testing hypotheses about past climate and validating climate models under varying climatic conditions. However, many models are run without explicitly simulating water isotopologues. We investigate the possibility of replacing the explicit physics-based simulation of oxygen isotopic composition in precipitation using machine learning methods. These methods estimate isotopic composition at each time step for given fields of surface temperature and precipitation amount. We implement convolutional neural networks (CNNs) based on the successful UNet architecture and test whether a spherical network architecture outperforms the naive approach of treating Earth’s latitude-longitude grid as a flat image. Conducting a case study on a last millennium run with the iHadCM3 climate model, we find that roughly 40% of the temporal variance in the isotopic composition is explained by the emulations on interannual and monthly timescale, with spatially varying emulation quality. The tested CNNs outperform simple baseline models such as random forest and pixel-wise linear regression substantially. A modified version of the standard UNet architecture for flat images yields results that are as good as the predictions by the spherical CNN. Variations in the implementation of isotopes between climate models likely contribute to an observed deterioration of emulation results when testing on data obtained from different climate models than the one used for training. Future work toward stable water-isotope emulation might focus on achieving robust climate–oxygen isotope relationships or exploring the set of possible predictor variables.
The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

We study the design decisions of publicly available instruction tuning methods, and break down the development of Flan 2022 (Chung et al., 2022). Through careful ablation studies on the Flan Collection of tasks and methods, we tease apart the effect of design decisions which enable Flan-T5 to outperform prior work by 3-17%+ across evaluation settings. We find task balancing and enrichment techniques are overlooked but critical to effective instruction tuning, and in particular, training with mixed prompt settings (zero-shot, few-shot, and chain-of-thought) actually yields stronger (2%+) performance in all settings. In further experiments, we show Flan-T5 requires less finetuning to converge higher and faster than T5 on single downstream tasks, motivating instruction-tuned models as more computationally-efficient starting checkpoints for new tasks. Finally, to accelerate research on instruction tuning, we make the Flan 2022 collection of datasets, templates, and methods publicly available at https://github.com/google-research/FLAN/tree/main/flan/v2.
Entanglement witnessing with untrusted detectors

We consider the problem of entanglement detection in the presence of faulty, potentially malicious detectors. A common—and, as of yet, the only—approach to this problem is to perform a Bell test in order to identify nonlocality of the measured entangled state. However, there are two significant drawbacks in this approach: the requirement to exceed a critical, and often high, detection efficiency, and much lower noise tolerance. In this paper, we propose an alternative approach to this problem, which is resilient to the detection loophole and is based on the standard tool of entanglement witness. We discuss how the two main techniques to detection losses, namely the discard and assignment strategies, apply to entanglement witnessing. We demonstrate using the example of a two-qubit Bell state that the critical detection efficiency can be significantly reduced compared to the Bell test approach.
Neutral hydrogen associated with shells and other fine structure in NGC 2865: A dynamically young elliptical?

We report the discovery of neutral hydrogen in a second elliptical galaxy with shells, NGC 2865. Very Large Array images reveal an association between the neutral hydrogen (H I) and the fine structure (shells, tails, and loops) in the galaxy. Similar to what we previously observed in NGC 5128 (Centaurus A), most of the 6 x 10(8) h(-2) M. of cold gas is found in a broken ring in the outer regions of NGC 2865 (beyond 1/2D(25))I and is displaced to the outside of the shells and loops. The measured velocities cover a range of 500 km s(-1) around the systemic velocity. The velocity field of the outer H I has the same sense and magnitude (and line of nodes) as that of the stars in the elliptical body. Although NGC 2865 appears to be a relaxed elliptical galaxy, deep images, photometry, and spectroscopy suggest that the galaxy might be the recent (less than 7 Gyr) product of a major disk-disk merger-a ''dynamically young elliptical. '' Our H I data support this hypothesis. Nevertheless, the association between gas and stellar fine structure, with gas displaced outward from the stars in projected position, implies gas motions not predicted by any of the current merger scenarios. Using the H I ring and assuming nearly circular motion, we measure M/L(B) at large radii (4 x 1/2D(25)). We find M/L(B) = 33 +/- 4 h, a factor of 5 greater than the value of M/L(B) found for the central regions, indicating the presence of a dark halo.
Quantized Neural Networks for Low-Precision Accumulation with Guaranteed Overflow Avoidance

We introduce a quantization-aware training algorithm that guarantees avoiding numerical overflow when reducing the precision of accumulators during inference. We leverage weight normalization as a means of constraining parameters during training using accumulator bit width bounds that we derive. We evaluate our algorithm across multiple quantized models that we train for different tasks, showing that our approach can reduce the precision of accumulators while maintaining model accuracy with respect to a floating-point baseline. We then show that this reduction translates to increased design efficiency for custom FPGA-based accelerators. Finally, we show that our algorithm not only constrains weights to fit into an accumulator of user-defined bit width, but also increases the sparsity and compressibility of the resulting weights. Across all of our benchmark models trained with 8-bit weights and activations, we observe that constraining the hidden layers of quantized neural networks to fit into 16-bit accumulators yields an average 98.2% sparsity with an estimated compression rate of 46.5x all while maintaining 99.2% of the floating-point performance.