Miracle-dz/UniFAR-FTUs huggingface dataset:
The Hercules cluster in X-rays with XMM-Newton and Chandra

We present a detailed X-ray study of the central subcluster of the nearby ($z$ $\sim$0.0368) Hercules cluster (Abell 2151) identified as A2151C that shows a bimodal structure. A bright clump of hot gas with X-ray emission extending to radius $r$ $\sim$304 kpc and $L_X = 3. 03_{-0.04}^{+0.02}\times10^{43}$ erg s$^{-1}$ in the 0.4$-$7.0 keV energy range is seen as a fairly regular subclump towards the west (A2151C(B)). An irregular, fainter and cooler subclump with radius $r$ $\sim$364 kpc is seen towards the east (A2151C(F)) and has $L_X=1.13\pm{0.02}\times10^{43}$ erg s$^{-1}$ in the 0.4$-$7.0 keV energy band. The average temperature and elemental abundance of A2151C(B) are $2.01\pm{0.05}$ keV and $0.43\pm{0.05}$ Z$_{\odot}$ respectively, while these values are $1.17\pm{0.04}$ keV and $0.13\pm{0.02}$ Z$_{\odot}$ for A2151C(F). Low temperature (${1.55}\pm{0.07}$ keV) and a short cooling time ($\sim$0.81 Gyr) within the central 15 arcsec region confirm the presence of a cool core in A2151C(B). We identify several compact groups of galaxies within A2151C(F). We find that A2151C(F) is a distinct galaxy group in the process of formation and likely not a ram-pressure stripped part of the eastern subcluster in Hercules (A2151E). X-ray emission from A2151C shows a region of overlap between A2151C(B) and A2151C(F) but without any enhancement of temperature or entropy in the two-dimensional (2D) projected thermodynamic maps that could have indicated an interaction due to merger between the two subclumps.
Genetic and genomic evaluation of claw health traits in Spanish dairy cattle

The purposes of this study were to implement a routine genetic evaluation of claw health traits and to validate the genomic proofs for six claw disorders: dermatitis (DE), sole ulcer (SU), white line disease (WL), concave dorsal wall (CD), interdigital phlegmon (IP), and interdigital hyperplasia (IH). Claw disorders show moderate to high negative correlations with five feet and legs conformation traits, feet & legs (F&L), rear legs rear view (RLRV), foot angle (FA), locomotion (LOC), and bone quality (BQ), which ranged from 0.23 to -0.90. Including feet and legs type traits in a multi-trait evaluation would be a good option in order to increase the reliability of claw health breeding values. Claw trimming information with 593 137 records of six claw disorders of 221 266 cows, daughters of 8 000 bulls, and recorded in 1 418 Holstein dairy herds by 34 trimmers were used to carry out a genetic evaluation for claw disorders considering two scenarios. The first one, a 6-trait analysis with the claw health traits, and in the second one, the type traits were added to the multi-trait analysis. A total claw health index (ISP) was used to compare the results using sires with at least 20 daughters and 50% of reliability. For genomic prediction, a GBLUP with polygenic effect was applied to estimate genomic breeding values. The 1 317 sires reaching a minimum of 50% in reliability of EBV for total claw health index were used as the reference population was applied to estimate genomic breeding values. The inclusion of feet and legs type traits in the multi-trait genetic evaluation increased the reliabilities for claw disorders EBV of proven sires by 8% to 32%. Regarding genomic validation, the correlations between DRP and DGV ranged from 0.15 to 0.36. The regression coefficients were close to 1, except for DE and IH. To achieve a higher accuracy a larger reference population is needed. Therefore, an international genetic evaluation for claw health would increase the sire’s reference population. At national level, performing a single-step evaluation could lead to slightly higher reliability.
Induction of Cardiomyocyte-Like Cells in Infarct Hearts by Gene Transfer of Gata4, Mef2c, and Tbx5

Rationale:After myocardial infarction (MI), massive cell death in the myocardium initiates fibrosis and scar formation, leading to heart failure. We recently found that a combination of 3 cardiac transcription factors, Gata4, Mef2c, and Tbx5 (GMT), reprograms fibroblasts directly into functional cardiomyocytes in vitro. Objective:To investigate whether viral gene transfer of GMT into infarcted hearts induces cardiomyocyte generation. Methods and Results:Coronary artery ligation was used to generate MI in the mouse. In vitro transduction of GMT retrovirus converted cardiac fibroblasts from the infarct region into cardiomyocyte-like cells with cardiac-specific gene expression and sarcomeric structures. Injection of the green fluorescent protein (GFP) retrovirus into mouse hearts, immediately after MI, infected only proliferating noncardiomyocytes, mainly fibroblasts, in the infarct region. The GFP expression diminished after 2 weeks in immunocompetent mice but remained stable for 3 months in immunosuppresse.
Functional diversification of hybridoma-produced antibodies by CRISPR/HDR genomic engineering

We develop a universal platform for CRISPR/HDR-engineering of hybridomas to obtain functionally diverse antibody panels. Hybridoma technology is instrumental for the development of novel antibody therapeutics and diagnostics. Recent preclinical and clinical studies highlight the importance of antibody isotype for therapeutic efficacy. However, since the sequence encoding the constant domains is fixed, tuning antibody function in hybridomas has been restricted. Here, we demonstrate a versatile CRISPR/HDR platform to rapidly engineer the constant immunoglobulin domains to obtain recombinant hybridomas, which secrete antibodies in the preferred format, species, and isotype. Using this platform, we obtained recombinant hybridomas secreting Fab′ fragments, isotype-switched chimeric antibodies, and Fc-silent mutants. These antibody products are stable, retain their antigen specificity, and display their intrinsic Fc-effector functions in vitro and in vivo. Furthermore, we can site-specifically attach cargo to these antibody products via chemoenzymatic modification. We believe that this versatile platform facilitates antibody engineering for the entire scientific community, empowering preclinical antibody research.
Drought-Affected Populus simonii Carr. Show Lower Growth and Long-Term Increases in Intrinsic Water-Use Efficiency Prior to Tree Mortality

The Three-North Shelter Forest (TNSF) is a critical ecological barrier against sandstorms in northern China, but has shown extensive decline and death in Populus simonii Carr. in the last decade. We investigated the characteristics—tree-ring width, basal area increment (BAI), carbon isotope signature (13Ccor), and intrinsic water-use efficiency (iWUE)—of now-dead, dieback, and non-dieback trees in TNSF shelterbelts of Zhangbei County. Results from the three groups were compared to understand the long-term process of preceding drought-induced death and to identify potential early-warning proxies of drought-triggered damage. The diameter at breast height (DBH) was found to decrease with the severity of dieback, showing an inverse relationship. In all three groups, both tree-ring width and BAI showed quadratic relationships with age, and peaks earlier in the now-dead and dieback groups than in the non-dieback group. The tree-ring width and BAI became significantly lower in the now-dead and dieback groups than in the non-dieback group from 17 to 26 years before death, thus, these parameters can serve as early-warning signals for future drought-induced death. The now-dead and dieback groups had significantly higher δ13Ccor and iWUEs than the non-dieback group at 7–16 years prior to the mortality, indicating a more conservative water-use strategy under drought stress compared with non-dieback trees, possibly at the cost of canopy defoliation and long-term shoot dieback. The iWUE became significantly higher in the now-dead group than in the dieback group at 0–7 years before death, about 10 years later than the divergence of BAI. After the iWUE became significantly different among the groups, the now-dead trees showed lower growth and died over the next few years. This indicates that, for the TNSF shelterbelts studied, an abrupt iWUE increase can be used as a warning signal for acceleration of impending drought-induced tree death. In general, we found that long-term drought decreased growth and increased iWUE of poplar tree. Successive droughts could drive dieback and now-dead trees to their physiological limits of drought tolerance, potentially leading to decline and mortality episodes.
Incentives to Form Larger Coalitions when Players Have the Power to Choose

We study a cooperative game setting where the grand coalition may change since the initial players are willing to invite their neighbours and also want to incentivize them to invite more players to join. We focus on the monotone games, i.e., adding more players to the grand coalition is not harmful. We model the invitation relationship as a forest since we require that each player can only accept the invitation at most once. Our goal is to design a solution mechanism to this new cooperative game setting. In this paper, we characterize the weighted permission Shapley value (inspired by permission structure and the weighted Shapley value), which is diffusion incentive compatible, i.e., all players are incentivized to invite their neighbours to join the coalition. Our solution offers the very first attempt to incentivize players to invite more players to form a larger coalition via their private connections, which has many potential applications in other real-world.
Virus Movement from Infected Sweetpotato Vines to Roots and Reversion on Root Sprouts

Sweetpotato is usually propagated in Uganda by vine cuttings from mature crops, but sometimes sprouts from storage roots are used, especially in drought-prone areas. No information is available on whether the storage of roots of Ugandan cultivars are infected with the viruses and whether the sprouts on them express symptoms so that farmers can eliminate diseased ones. Information on root sprout reversion from virus infection is also lacking. The storage roots of five sweetpotato cultivars was sourced either by random selection of roots from already harvested roots or obtained from symptomless plants selected before harvest at Makerere University Agricultural Research Institute, Kabanyolo (MUARIK), and the National Semi Arid Resources Research Institute (NaSARRI). Roots were also generated in a screenhouse after being inoculated with Sweet potato feathery mottle virus (SPFMV) and/or Sweet potato chlorotic stunt virus (SPCSV). More than 70% of sprouts from roots of all the cultivars selected after harvest at MUARIK and NaSARRI were infected with the viruses. For roots obtained from symptomless plants, 64% and 21% of the sprouted roots from MUARIK and NaSARRI were infected with the viruses, respectively. Most of the root samples from MUARIK had visible virus symptoms on sprouts and tested positive for both SPFMV and SPCSV, whereas those from NaSARRI did not show symptoms and were infected primarily with SPFMV. Plants graft-inoculated with either SPCSV or SPFMV alone produced both infected and noninfected roots, whereas all the root sprouts from dually infected plants showed virus symptoms. Reversion from virus infection was observed on root sprouts infected singly with SPFMV, whereas those infected with SPCSV showed recovery only, and none of the root sprouts infected by both viruses showed recovery. This study proves that roots are good reservoirs for viruses, and reversion occurs only when singly infected with SPFMV. Therefore, there is a need to establish seed channels in which seedstock is cleaned continuously and made available to farmers.
Multigrid-in-Channels Neural Network Architectures

We present a multigrid-in-channels (MGIC) approach that tackles the quadratic growth of the number of parameters with respect to the number of channels in standard convolutional neural networks (CNNs). It has been shown that there is a redundancy in standard CNNs, as networks with light or sparse convolution operators yield similar performance to full networks. However, the number of parameters in the former networks also scales quadratically in width, while in the latter case, the parameters typically have random sparsity patterns, hampering hardware efficiency.Our approach for building CNN architectures scales linearly with respect to the network's width while retaining full coupling of the channels as in standard this http URL this end, we replace each convolution block with its MGIC block utilizing a hierarchy of lightweight convolutions. Our extensive experiments on image classification, segmentation, and point cloud classification show that applying this strategy to different architectures like ResNet and MobileNetV3 considerably reduces the number of parameters while obtaining similar or better accuracy. For example, we obtain 76.1% top-1 accuracy on ImageNet with a lightweight network with similar parameters and FLOPs to MobileNetV3.
Deep Networks for Direction-of-Arrival Estimation in Low SNR

In this work, we consider direction-of-arrival (DoA) estimation in the presence of extreme noise using Deep Learning (DL). In particular, we introduce a Convolutional Neural Network (CNN) that predicts angular directions using the sample covariance matrix estimate. The network is trained from multi-channel data of the true array manifold matrix in the low signal-to-noise-ratio (SNR) regime. By adopting an on-grid approach, we model the problem as a multi-label classification task and train the CNN to predict DoAs across all SNRs. The proposed architecture demonstrates enhanced robustness in the presence of noise, and resilience to a relatively small number of snapshots. Moreover, it is able to resolve angles within the grid resolution. Experimental results demonstrate significant performance gains in the low-SNR regime compared to state-of-the-art methods and without the requirement of any parameter tuning in both cases of correlated and uncorrelated sources. Finally, we relax the assumption that the number of sources is known a priori and present a training method, where the CNN learns to infer their number and predict the DoAs with high confidence. The increased robustness of the proposed solution is highly desirable in challenging scenarios that arise in several fields, ranging from wireless array sensors to acoustic microphones or sonars.
DeepNAG: Deep Non-Adversarial Gesture Generation

Synthetic data generation to improve classification performance (data augmentation) is a well-studied problem. Recently, generative adversarial networks (GAN) have shown superior image data augmentation performance, but their suitability in gesture synthesis has received inadequate attention. Further, GANs prohibitively require simultaneous generator and discriminator network training. We tackle both issues in this work. We first discuss a novel, device-agnostic GAN model for gesture synthesis called DeepGAN. Thereafter, we formulate DeepNAG by introducing a new differentiable loss function based on dynamic time warping and the average Hausdorff distance, which allows us to train DeepGAN’s generator without requiring a discriminator. Through evaluations, we compare the utility of DeepGAN and DeepNAG against two alternative techniques for training five recognizers using data augmentation over six datasets. We further investigate the perceived quality of synthesized samples via an Amazon Mechanical Turk user study based on the HYPE∞ benchmark. We find that DeepNAG outperforms DeepGAN in accuracy, training time (up to 17 × faster), and realism, thereby opening the door to a new line of research in generator network design and training for gesture synthesis. Our source code is available at https://www.deepnag. com.
Semantic Scene Completion Using Local Deep Implicit Functions on LiDAR Data

Semantic scene completion is the task of jointly estimating 3D geometry and semantics of objects and surfaces within a given extent. This is a particularly challenging task on real-world data that is sparse and occluded. We propose a scene segmentation network based on local Deep Implicit Functions as a novel learning-based method for scene completion. Unlike previous work on scene completion, our method produces a continuous scene representation that is not based on voxelization. We encode raw point clouds into a latent space locally and at multiple spatial resolutions. A global scene completion function is subsequently assembled from the localized function patches. We show that this continuous representation is suitable to encode geometric and semantic properties of extensive outdoor scenes without the need for spatial discretization (thus avoiding the trade-off between level of scene detail and the scene extent that can be covered). We train and evaluate our method on semantically annotated LiDAR scans from the Semantic KITTI dataset. Our experiments verify that our method generates a powerful representation that can be decoded into a dense 3D description of a given scene. The performance of our method surpasses the state of the art on the Semantic KITTI Scene Completion Benchmark in terms of geometric completion intersection-over-union (IoU).
Host density predicts the probability of parasitism by avian brood parasites

The spatial distribution of hosts can be a determining factor in the reproductive success of parasites. Highly aggregated hosts may offer more opportunities for reproduction but can have better defences than isolated hosts. Here we connect macro- and micro-evolutionary processes to understand the link between host density and parasitism, using avian brood parasites as a model system. We analyse data across more than 200 host species using phylogenetic comparative analyses and quantify parasitism rate and host reproductive success in relation to spatial distribution using field data collected on one host species over 6 years. Our comparative analysis reveals that hosts occurring at intermediate densities are more likely to be parasitized than colonial or widely dispersed hosts. Correspondingly, our intraspecific field data show that individuals living at moderate densities experience higher parasitism rates than individuals at either low or high densities. Moreover, we show for the first time that the effect of host density on host reproductive success varies according to the intensity of parasitism; hosts have greater reproductive success when living at high densities if parasitism rates are high, but fare better at low densities when parasitism rates are low. We provide the first evidence of the trade-off between host density and parasitism at both macro- and micro-evolutionary scales in brood parasites. This article is part of the theme issue ‘The coevolutionary biology of brood parasitism: from mechanism to pattern’.
Vertical-Horizontal Structured Attention for Generating Music with Chords

In this paper, we propose a lightweight music-generating model based on variational autoencoder (VAE) with structured attention. Generating music is different from generating text because the melodies with chords give listeners distinguished polyphonic feelings. In a piece of music, a chord consisting of multiple notes comes from either the mixture of multiple instruments or the combination of multiple keys of a single instrument. We focus our study on the latter. Our model captures not only the temporal relations along time but the structure relations between keys. Experimental results show that our model has a better performance than baseline MusicVAE in capturing notes in a chord. Besides, our method accords with music theory since it maintains the configuration of the circle of fifths, distinguishes major and minor keys from interval vectors, and manifests meaningful structures between music phrases.
Análisis estructural de un área agroforestal en una porción del matorral xerófilo del noreste de México

Background and Aims: The studies of plant communities allow to know the impacts caused by the agricultural and livestock activities, especially in arid zones. The objective of this work was to contrast the diversity, composition and structure of the arboreal and shrub strata of three areas (Agroforestry, Regenerated and Reference) of the xerophilous scrub. Methods: In each area four sampling sites of 1600 m 2 each one were established randomly, where all arboreal and shrubby individuals were registered and censused. In each area, ecological parameters were calculated, as well as the Shannon and Margalef indices. Key results: In the three areas, a total of 25 species of vascular plants belonging to 22 genera and 15 families were registered. The best represented family was Fabaceae with nine species, being the genus Acacia the one that presented the largest species number (three). The observed values of species richness, the Shannon index, Margalef index and abundance between the Reference and Agroforestry area were similar, and both were significantly higher than the values of the Regenerated area. The Agroforestry area presented lower abundance but greater dominance compared with the other two areas studied, and it was the area that reached the highest percentage of similarity with the Reference area. Conclusions: The Agroforestry activity contributes in a certain way in the maintenance of the diversity and composition of vascular plants of the Tamaulipan thorn scrub studied; and this activity does not allow to change to a large extent the composition and structure of this type of vegetation.
Muscle mechanics and energy expenditure of the triceps surae during rearfoot and forefoot running

Forefoot running is advocated to improve running economy because of increased elastic energy storage than rearfoot running. This claim has not been assessed with methods that predict the elastic energy contribution to positive work or estimate muscle metabolic cost. The purpose of this study was to compare the mechanical work and metabolic cost of the gastrocnemius and soleus between rearfoot and forefoot running. Seventeen rearfoot and seventeen forefoot runners ran over-ground with their habitual footfall pattern (3.33-3.68m•s−1) while collecting motion capture and ground reaction force data. Ankle and knee joint angles and ankle joint moments served as inputs into a musculoskeletal model that calculated the mechanical work and metabolic energy expenditure of each muscle using Hill-based muscle models with contractile (CE) and series elastic (SEE) elements. A mixed-factor ANOVA assessed the difference between footfall patterns and groups (α=0.05). Forefoot running resulted in greater SEE mechanical work in the gastrocnemius than rearfoot running but no differences were found in CE mechanical work or CE metabolic energy expenditure. Forefoot running resulted in greater soleus SEE and CE mechanical work and CE metabolic energy expenditure than rearfoot running. The metabolic cost associated with greater CE velocity, force production, and activation during forefoot running may outweigh any metabolic energy savings associated with greater SEE mechanical work. Therefore, there was no energetic benefit at the triceps surae for one footfall pattern or the other. The complex CE-SEE interactions must be considered when assessing muscle metabolic cost, not just the amount of SEE strain energy.