Miracle-dz/UniFAR-FTUs huggingface dataset:
In and out of glacial extremes by way of dust−climate feedbacks

Significance In observational data, we find striking and globally coherent increases of atmospheric dust concentrations and deposition during the coldest phases of glacial−interglacial climate cycles. As shown by our simulations with a climate−carbon cycle model, such a relationship between dust and climate implies that dust-induced cooling is responsible for the final step from intermediate to extreme glacial cooling and drawdown of atmospheric CO2 concentrations. These results also increase our overall understanding of glacial−interglacial cycles by putting further constraints on the timing and strength of other processes involved in these cycles, like changes in sea ice and ice sheet extents or changes in ocean circulation and deep water formation. Mineral dust aerosols cool Earth directly by scattering incoming solar radiation and indirectly by affecting clouds and biogeochemical cycles. Recent Earth history has featured quasi-100,000-y, glacial−interglacial climate cycles with lower/higher temperatures and greenhouse gas concentrations during glacials/interglacials. Global average, glacial maxima dust levels were more than 3 times higher than during interglacials, thereby contributing to glacial cooling. However, the timing, strength, and overall role of dust−climate feedbacks over these cycles remain unclear. Here we use dust deposition data and temperature reconstructions from ice sheet, ocean sediment, and land archives to construct dust−climate relationships. Although absolute dust deposition rates vary greatly among these archives, they all exhibit striking, nonlinear increases toward coldest glacial conditions. From these relationships and reconstructed temperature time series, we diagnose glacial−interglacial time series of dust radiative forcing and iron fertilization of ocean biota, and use these time series to force Earth system model simulations. The results of these simulations show that dust−climate feedbacks, perhaps set off by orbital forcing, push the system in and out of extreme cold conditions such as glacial maxima. Without these dust effects, glacial temperature and atmospheric CO2 concentrations would have been much more stable at higher, intermediate glacial levels. The structure of residual anomalies over the glacial−interglacial climate cycles after subtraction of dust effects provides constraints for the strength and timing of other processes governing these cycles.
APATITE FORMATION ON COBALT AND TITANIUM ALLOYS BY A BIOMIMETIC PROCESS

Ti and Co alloys were subjected to a biomimetic process. The Ti and Co alloy samples were immersed in 10M and 5M NaOH solutions, respectively. The samples were heat treated and finally, immersed in either a simulated body fluid (SBF) with a lower ionic concentration to that of human blood plasma (0.85SBF) or a simulated body fluid with a higher ionic concentration (1.3SBF) for a period of 21 days. A more modified surface, due to the chemical and heat treatment, was observed on the Ti alloys than on the Co alloys. An apatite layer was observed after the immersion of the samples in 0.85SBF for both, Ti and Co alloys. After the immersion in 0.85SBF the observed ceramic layer on the Ti alloy samples was more homogeneous and thicker than that observed on the Co alloy samples. However, the ceramic layer on both samples was not continuous along the surface. A thick apatite layer was formed on samples immersed in 1.3SBF and this was attributed to the higher ion concentration, mainly of calcium and phosphoms. The CdP ratios measured in the apatite layers formed in 1.3SBF were closer to that of bone. (KEY WORDS: Apatite, Bioactive, Biomimetic, Simulated Body Fluid)
Investigating Word Affect Features and Fusion of Probabilistic Predictions Incorporating Uncertainty in AVEC 2017

Predicting emotion intensity and severity of depression are both challenging and important problems within the broader field of affective computing. As part of the AVEC 2017, we developed a number of systems to accomplish these tasks. In particular, word affect features, which derive human affect ratings (e.g. arousal and valence) from transcripts, were investigated for predicting depression severity and liking, showing great promise. A simple system based on the word affect features achieved an RMSE of 6.02 on the test set, yielding a relative improvement of 13.6% over the baseline. For the emotion prediction sub-challenge, we investigated multimodal fusion, which incorporated a measure of uncertainty associated with each prediction within an Output-Associative fusion framework for arousal and valence prediction, whilst liking prediction systems mainly focused on text-based features. Our best emotion prediction systems provided significant relative improvements over the baseline on the test set of 39.5%, 17.6%, and 29.3% for arousal, valence, and liking. Of particular note is that consistent improvements were observed when incorporating prediction uncertainty across various system configurations for predicting arousal and valence, suggesting the importance of taking into consideration prediction uncertainty for fusion and more broadly the advantages of probabilistic predictions.
Co-simulation of an interior permanent magnet synchronous motor with segmented rotor structure

Accurate simulation of electric drives has always been desirable, as it allows the machine designer a deeper insight into the whole design. It is known that a co-simulation of Finite-Element-Analysis, circuit and control simulation can give much more accurate results than conventional simulation approaches. The effects of rotor segmentation, however, cannot be accurately modeled in two dimensions. Through introduction of a multi-slice approach to the co-simulation motors with segmented rotor structures can be analyzed even with a two-dimensional Finite-Element-Method approach. This publication presents a co-simulation of a permanent magnet synchronous drive, also taking the rotor segmentation into consideration with a two-dimensional multi-slice approach. The comparison of the simulation results with test bench measurements shows a good correspondence. Accuracy improvements of the results of the multi-slice approach in comparison to an unsegmented rotor structure as well as simulations with fundamental wave models are obvious.
Robust DLPP With Nongreedy $\ell _1$ -Norm Minimization and Maximization

Recently, discriminant locality preserving projection based on L1-norm (DLPP-L1) was developed for robust subspace learning and image classification. It obtains projection vectors by greedy strategy, i.e., all projection vectors are optimized individually through maximizing the objective function. Thus, the obtained solution does not necessarily best optimize the corresponding trace ratio optimization algorithm, which is the essential objective function for general dimensionality reduction. It results in insufficient recognition accuracy. To tackle this problem, we propose a nongreedy algorithm to solve the trace ratio formula of DLPP-L1, and analyze its convergence. Experimental results on three databases illustrate the effectiveness of our proposed algorithm.
A Variational Inequality Perspective on Generative Adversarial Networks

Generative adversarial networks (GANs) form a generative modeling approach known for producing appealing samples, but they are notably difficult to train. One common way to tackle this issue has been to propose new formulations of the GAN objective. Yet, surprisingly few studies have looked at optimization methods designed for this adversarial training. In this work, we cast GAN optimization problems in the general variational inequality framework. Tapping into the mathematical programming literature, we counter some common misconceptions about the difficulties of saddle point optimization and propose to extend techniques designed for variational inequalities to the training of GANs. We apply averaging, extrapolation and a computationally cheaper variant that we call extrapolation from the past to the stochastic gradient method (SGD) and Adam.
Convolutional Neural Network-Based Robot Navigation Using Uncalibrated Spherical Images

Vision-based mobile robot navigation is a vibrant area of research with numerous algorithms having been developed, the vast majority of which either belong to the scene-oriented simultaneous localization and mapping (SLAM) or fall into the category of robot-oriented lane-detection/trajectory tracking. These methods suffer from high computational cost and require stringent labelling and calibration efforts. To address these challenges, this paper proposes a lightweight robot navigation framework based purely on uncalibrated spherical images. To simplify the orientation estimation, path prediction and improve computational efficiency, the navigation problem is decomposed into a series of classification tasks. To mitigate the adverse effects of insufficient negative samples in the “navigation via classification” task, we introduce the spherical camera for scene capturing, which enables 360° fisheye panorama as training samples and generation of sufficient positive and negative heading directions. The classification is implemented as an end-to-end Convolutional Neural Network (CNN), trained on our proposed Spherical-Navi image dataset, whose category labels can be efficiently collected. This CNN is capable of predicting potential path directions with high confidence levels based on a single, uncalibrated spherical image. Experimental results demonstrate that the proposed framework outperforms competing ones in realistic applications.
Exercise reestablishes autophagic flux and mitochondrial quality control in heart failure

ABSTRACT We previously reported that facilitating the clearance of damaged mitochondria through macroautophagy/autophagy protects against acute myocardial infarction. Here we characterize the impact of exercise, a safe strategy against cardiovascular disease, on cardiac autophagy and its contribution to mitochondrial quality control, bioenergetics and oxidative damage in a post-myocardial infarction-induced heart failure animal model. We found that failing hearts displayed reduced autophagic flux depicted by accumulation of autophagy-related markers and loss of responsiveness to chloroquine treatment at 4 and 12 wk after myocardial infarction. These changes were accompanied by accumulation of fragmented mitochondria with reduced O2 consumption, elevated H2O2 release and increased Ca2+-induced mitochondrial permeability transition pore opening. Of interest, disruption of autophagic flux was sufficient to decrease cardiac mitochondrial function in sham-treated animals and increase cardiomyocyte toxicity upon mitochondrial stress. Importantly, 8 wk of exercise training, starting 4 wk after myocardial infarction at a time when autophagy and mitochondrial oxidative capacity were already impaired, improved cardiac autophagic flux. These changes were followed by reduced mitochondrial number:size ratio, increased mitochondrial bioenergetics and better cardiac function. Moreover, exercise training increased cardiac mitochondrial number, size and oxidative capacity without affecting autophagic flux in sham-treated animals. Further supporting an autophagy mechanism for exercise-induced improvements of mitochondrial bioenergetics in heart failure, acute in vivo inhibition of autophagic flux was sufficient to mitigate the increased mitochondrial oxidative capacity triggered by exercise in failing hearts. Collectively, our findings uncover the potential contribution of exercise in restoring cardiac autophagy flux in heart failure, which is associated with better mitochondrial quality control, bioenergetics and cardiac function.
ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages

We present ABRA, a suite of algorithms to compute and maintain probabilistically-guaranteed, high-quality, approximations of the betweenness centrality of all nodes (or edges) on both static and fully dynamic graphs. Our algorithms use progressive random sampling and their analysis rely on Rademacher averages and pseudodimension, fundamental concepts from statistical learning theory. To our knowledge, this is the first application of these concepts to the field of graph analysis. Our experimental results show that ABRA is much faster than exact methods, and vastly outperforms, in both runtime and number of samples, state-of-the-art algorithms with the same quality guarantees.
Why is gynodioecy a rare but widely distributed sexual system? Lessons from the Lamiaceae.

Gynodioecy, a sexual system where females and hermaphrodites co-occur, is found in << 1% of angiosperm species. To understand why gynodioecy is rare, we need to understand why females are maintained in some lineages, but not in others. We modelled the evolution of gynodioecy in the Lamiaceae, and investigated whether transition rates between gynodioecious and nongynodioecious states varied across the family. We also investigated whether the evolution of gynodioecy was correlated with the evolution of a herbaceous growth form and temperate distribution. Transition rates differed between Lamiaceae subfamilies. In the Nepetoideae, there were many transitions towards gynodioecy (n = 11), but also many reversions to nongynodioecy (n = 29). In addition, a herbaceous growth form, but not a temperate distribution, affected the rate of transitions both towards and away from gynodioecy; transitions towards gynodioecy occurred ˜16 times more frequently and transitions away from gynodioecy occurred ˜11 times more frequently in herbaceous lineages than in woody lineages. Within the Lamiaceae, lineages in which gynodioecy has frequently evolved also have a high rate of reversions to the nongynodioecious state. Consequently, to understand why gynodioecy is rare, we need to understand why sexual systems are more evolutionarily labile in some lineages than in others.
Short-term outcomes predictors of hip arthroscopy in male patients aged 50 or younger

Introduction TStudies of arthroscopic treatment in Femoroace tabular impingement (FAI) show improvement in pain, activities of daily living and sports [1-3]. Currently, the numbers of HA continues to grow in young active population. Philippon reported that in patients aged 50 years or older with joint space lower than 2 mm and low preoperative mHHS, early conversion to total hip replacement was seen[4]. But, are these variables useful in younger patients? This study of a consecutive series of male patients aged 50 years or younger had the purpose to investigate, which factor is the main contributor to pain and decreased function after HA. We hypothesized that patients with 2 mm of joint space or less, and low preoperative mhhs, would have unsuccessful clinical results and the need for revision surgery. Abstract
Development and application of a recombination-based library versus library high- throughput yeast two-hybrid (RLL-Y2H) screening system

Abstract Protein-protein interaction (PPI) network maintains proper function of all organisms. Simple high-throughput technologies are desperately needed to delineate the landscape of PPI networks. While recent state-of-the-art yeast two-hybrid (Y2H) systems improved screening efficiency, either individual colony isolation, library preparation arrays, gene barcoding or massive sequencing are still required. Here, we developed a recombination-based ‘library vs library’ Y2H system (RLL-Y2H), by which multi-library screening can be accomplished in a single pool without any individual treatment. This system is based on the phiC31 integrase-mediated integration between bait and prey plasmids. The integrated fragments were digested by MmeI and subjected to deep sequencing to decode the interaction matrix. We applied this system to decipher the trans-kingdom interactome between Mycobacterium tuberculosis and host cells and further identified Rv2427c interfering with the phagosome–lysosome fusion. This concept can also be applied to other systems to screen protein–RNA and protein–DNA interactions and delineate signaling landscape in cells.
Frontal Oscillatory Dynamics Predict Feedback Learning and Action Adjustment

Frontal oscillatory dynamics in the theta (4–8 Hz) and beta (20–30 Hz) frequency bands have been implicated in cognitive control processes. Here we investigated the changes in coordinated activity within and between frontal brain areas during feedback-based response learning. In a time estimation task, participants learned to press a button after specific, randomly selected time intervals (300–2000 msec) using the feedback after each button press (correct, too fast, too slow). Consistent with previous findings, theta-band activity over medial frontal scalp sites (presumably reflecting medial frontal cortex activity) was stronger after negative feedback, whereas beta-band activity was stronger after positive feedback. Theta-band power predicted learning only after negative feedback, and beta-band power predicted learning after positive and negative feedback. Furthermore, negative feedback increased theta-band intersite phase synchrony (a millisecond resolution measure of functional connectivity) among right lateral prefrontal, medial frontal, and sensorimotor sites. These results demonstrate the importance of frontal theta- and beta-band oscillations and intersite communication in the realization of reinforcement learning.
Development and validation of a quantitative snack and beverage food frequency questionnaire for adolescents

BACKGROUND A short, reliable and valid tool to measure snack and beverage consumption in adolescents, taking into account the correct definitions, would benefit both epidemiological and intervention research. The present study aimed to develop a short quantitative beverage and snack food frequency questionnaire (FFQ) and to assess the reliability and validity of this FFQ against three 24-h recalls. METHODS Reliability was assessed by comparing estimates of the FFQ administered 14 days apart (FFQ1 and FFQ2) in a convenience sample of 179 adolescents [60.3% male; mean (SD) 14.7 (0.9) years]. Validity was assessed by comparing FFQ1 with three telephone-administered 24-h recalls in a convenience sample of 99 adolescents [52.5% male, mean (SD) 14.8 (0.9) years]. Reliability and validity were assessed using Bland-Altman plots, classification agreements and correlation coefficients for the amount and frequency of consumption of unhealthy snacks, healthy snacks, unhealthy beverages, healthy beverages, and for the healthy snack and beverage ratios. RESULTS Small mean differences (FFQ1 versus FFQ2) were observed for reliability, ranking ability ranged from fair to substantial, and Spearman coefficients fell within normal ranges. For the validity, mean differences (FFQ1 versus recalls) were small for beverage intake but large for snack intake, except for the healthy snack ratio. Ranking ability ranged from slightly to moderate, and Spearman coefficients fell within normal ranges. CONCLUSIONS Reliability and validity of the FFQ for all outcomes were found to be acceptable at a group level for epidemiological purposes, whereas for intervention purposes only the healthy snack and beverage ratios were found to be acceptable at a group level.
Respiratory syncytial virus-like nanoparticle vaccination induces long-term protection without pulmonary disease by modulating cytokines and T-cells partially through alveolar macrophages

The mechanisms of protection against respiratory syncytial virus (RSV) are poorly understood. Virus-like nanoparticles expressing RSV glycoproteins (eg, a combination of fusion and glycoprotein virus-like nanoparticles [FG VLPs]) have been suggested to be a promising RSV vaccine candidate. To understand the roles of alveolar macrophages (AMs) in inducing long-term protection, mice that were 12 months earlier vaccinated with formalin-inactivated RSV (FI-RSV) or FG VLPs were treated with clodronate liposome prior to RSV infection. FI-RSV immune mice with clodronate liposome treatment showed increases in eosinophils, plasmacytoid dendritic cells, interleukin (IL)-4+ T-cell infiltration, proinflammatory cytokines, chemokines, and, in particular, mucus production upon RSV infection. In contrast to FI-RSV immune mice with severe pulmonary histopathology, FG VLP immune mice showed no overt sign of histopathology and significantly lower levels of eosinophils, T-cell infiltration, and inflammatory cytokines, but higher levels of interferon-γ, which are correlated with protection against RSV disease. FG VLP immune mice with depletion of AMs showed increases in inflammatory cytokines and chemokines, as well as eosinophils. The results in this study suggest that FG nanoparticle vaccination induces long-term protection against RSV and that AMs play a role in the RSV protection by modulating eosinophilia, mucus production, inflammatory cytokines, and T-cell infiltration.
BMP-Responsive Protease HtrA1 Is Differentially Expressed in Astrocytes and Regulates Astrocytic Development and Injury Response

Astrocytes perform a wide array of physiological functions, including structural support, ion exchange, and neurotransmitter uptake. Despite this diversity, molecular markers that label subpopulations of astrocytes are limited, and mechanisms that generate distinct astrocyte subtypes remain unclear. Here we identified serine protease high temperature requirement A 1 (HtrA1), a bone morphogenetic protein 4 signaling regulated protein, as a novel marker of forebrain astrocytes, but not of neural stem cells, in adult mice of both sexes. Genetic deletion of HtrA1 during gliogenesis accelerates astrocyte differentiation. In addition, ablation of HtrA1 in cultured astrocytes leads to altered chondroitin sulfate proteoglycan expression and inhibition of neurite extension, along with elevated levels of transforming growth factor-β family proteins. Brain injury induces HtrA1 expression in reactive astrocytes, and loss of HtrA1 leads to an impairment in wound closure accompanied by increased proliferation of endothelial and immune cells. Our findings demonstrate that HtrA1 is differentially expressed in adult mouse forebrain astrocytes, and that HtrA1 plays important roles in astrocytic development and injury response. SIGNIFICANCE STATEMENT Astrocytes, an abundant cell type in the brain, perform a wide array of physiological functions. Although characterized as morphologically and functionally diverse, molecular markers that label astrocyte subtypes or signaling pathways that lead to their diversity remain limited. Here, after examining the expression profile of astrocytes generated in response to bone morphogenetic protein signaling, we identify high temperature requirement A 1 (HtrA1) as an astrocyte-specific marker that is differentially expressed in distinct adult mouse brain regions. HtrA1 is a serine protease that has been linked to cerebral autosomal recessive arteriopathy with subcortical infarcts and leukoencephalopathy, a small blood vessel disease in humans. Understanding the role of HtrA1 during development and after injury will provide insights into how distinct astrocyte populations are generated and their unique roles in injury and disease.