Miracle-dz/UniFAR-FTUs huggingface dataset:
Unveiling cells’ local environment during cryopreservation by correlative in situ spatial and thermal analyses

Cryopreservation is the only fully established procedure to extend the lifespan of living cells and tissues, a key to activities spanning from fundamental biology to clinical practice. Despite its prevalence and impact, central aspects of cryopreservation, such as the cell’s physico-chemical environment during freezing, remain elusive. Here we address that question by coupling in situ microscopic directional freezing to visualize cells and their surroundings during freezing with the freezing medium phase diagram. We extract the freezing medium spatial distribution in cryopreservation, providing a tool to describe the cell vicinity at any point during freezing. We show that two major events define the cells’ local environment over time: the interaction with the moving ice front and with the vitreous moving front – a term we introduce here. Our correlative strategy may be applied to cells relevant in clinical research and practice, and help designing new cryoprotective media based on local physico-chemical cues.
Large Deviations and Fluctuation Theorem for the Entropy Production Rate of a Stochastic Particle System in Magnetic Field

We prove a large deviation principle (LDP) and a fluctuation theorem (FT) for the entropy production rate (EPR) of the following $d$ dimensional stochastic differential equation \begin{equation*} d X_{t}=AX_{t} d t+\sqrt{Q} d B_{t} \end{equation*} where $A$ is a real normal stable matrix, $Q$ is positive definite, and the matrices $A$ and $Q$ commute. The rate function for the EPR takes the following explicit form: \begin{equation*} I(x)=\left\{ \begin{array}{ll} x\frac{\sqrt{1+\ell_0(x)}-1}{2}+\frac 12\sum\limits_{k=1}^{d} \left(\sqrt{\alpha_k^2- \beta_k^2\ell_0(x)}+\alpha_k\right) , & x\ge 0 , \\ -x\frac{\sqrt{1+\ell_0(x)}+1}{2} +\frac 12\sum\limits_{k=1}^{d} \left(\sqrt{\alpha_k^2- \beta_k^2\ell_0(x)}+\alpha_k\right) , &x<0, \end{array} \right. \end{equation*} where $\alpha_{k}\pm {\rm i} \beta_{k}$ are the eigenvalues of $A$, and $\ell_0(x)$ is the unique solution of the equation: \begin{align*} |x|={\sqrt{1+\ell}} \times \sum_{k=1}^{d} \frac{\beta_k^2}{\sqrt{\alpha_k^2 -\ell\beta_k^2} },\qquad -1 \le \ell< \min_{k=1,. ,d}\{\frac{\alpha_k^2}{\beta_k^2}\}. \end{align*} Simple closed form formulas for rate functions are rare and our work identifies an important class of large deviation problems where such formulas are available. The logarithmic moment generating function (the fluctuation function) $\Lambda$ associated with the LDP has a closed form (see it in the paper). The functions $\Lambda(\lambda)$ and $ I(x)$ satisfy the Cohen-Gallavotti symmetry properties. In particular, the functions $I$ and $\Lambda$ do not depend on the diffusion matrix $Q$, and are determined completely by the real and imaginary parts of the eigenvalues of $A$. Formally, the deterministic system with $Q=0$ has zero EPR and thus the model exhibits a phase transition in that the EPR changes discontinuously at $Q = 0$.
Mobility-Assisted Covert Communication over Wireless Ad Hoc Networks

We study the capacity scaling of the covert communication over a wireless ad hoc network where n mobile nodes want to communicate each other in a unit disk while keeping the presence of the communication secret from each of ⊝(ns) non-colluding wardens (0 < s < 1). We modify the two-hop based scheme by Grossglauser and Tse (2002), which is proposed for a wireless ad hoc network without a covertness constraint, by introducing a preservation region around each warden in which the senders are not allowed to transmit. This scheme is shown to be optimal under an assumption that each node outside the preservation regions uses the same transmit power. Our results show that the node mobility greatly improves the aggregate throughput, compared to the case of fixed node location. In particular, the aggregate throughput scaling is shown to be linear in n when the number of channel uses that each warden uses to judge the presence of communication is not too large compared to n.
CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT

The extraction of labels from radiology text reports enables large-scale training of medical imaging models. Existing approaches to report labeling typically rely either on sophisticated feature engineering based on medical domain knowledge or manual annotations by experts. In this work, we introduce a BERT-based approach to medical image report labeling that exploits both the scale of available rule-based systems and the quality of expert annotations. We demonstrate superior performance of a biomedically pretrained BERT model first trained on annotations of a rule-based labeler and then finetuned on a small set of expert annotations augmented with automated backtranslation. We find that our final model, CheXbert, is able to outperform the previous best rules-based labeler with statistical significance, setting a new SOTA for report labeling on one of the largest datasets of chest x-rays.
The formation of young massive clusters by colliding flows

Young massive clusters (YMCs) are the most intense regions of star formation in galaxies. Formulating a model for YMC formation while at the same time meeting the constraints from observations is, however, highly challenging. We show that forming YMCs requires clouds with densities ≳ 100 cm−3 to collide with high velocities (≳ 20 km s−1). We present the first simulations which, starting from moderate cloud densities of ∼100 cm−3, are able to convert a large amount of mass into stars over a time period of around 1 Myr, to produce dense massive clusters similar to those observed. Such conditions are commonplace in more extreme environments, where YMCs are common, but atypical for our Galaxy, where YMCs are rare.
Postural Control Adaptation and Habituation During Vibratory Proprioceptive Stimulation: An HD-EEG Investigation of Cortical Recruitment and Kinematics

The objective of the present work is to measure postural kinematics and power spectral variation from HD-EEG to assess changes in cortical activity during adaptation and habituation to postural perturbation. To evoke proprioceptive postural perturbation, vibratory stimulation at 85 Hz was applied to the calf muscles of 33 subjects over four 75-second stimulation periods. Stimulation was performed according to a pseudorandom binary sequence. Vibratory impulses were synchronized to high-density electroencephalography (HD-EEG, 256 channels). Changes in absolute spectral power (ASP) were analyzed over four frequency bands (<inline-formula> <tex-math notation="LaTeX">$ {\Delta }$ </tex-math></inline-formula>: 0.5–3.5 Hz; <inline-formula> <tex-math notation="LaTeX">$ {\theta }$ </tex-math></inline-formula>: 3.5–7.5 Hz; <inline-formula> <tex-math notation="LaTeX">$ {\alpha }$ </tex-math></inline-formula>: 7.5–12.5 Hz; <inline-formula> <tex-math notation="LaTeX">$ {\beta }$ </tex-math></inline-formula>: 12.5–30 Hz). A force platform recorded torque actuated by the feet, and normalized sway path length (SPL) was computed as a construct for postural performance during each period. SPL values indicated improvement in postural performance over the trial periods. Significant variation in absolute power values (ASP) was found in assessing postural adaptation: an increase in <inline-formula> <tex-math notation="LaTeX">$ {\theta }$ </tex-math></inline-formula> band ASP in the frontal-central region for closed-eyes trials, an increase in <inline-formula> <tex-math notation="LaTeX">$ {\theta }$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$ {\beta }$ </tex-math></inline-formula> band ASP in the parietal region for open-eyes trials. In habituation, no significant variations in ASP were observed during closed-eyes trials, whereas an increase in <inline-formula> <tex-math notation="LaTeX">$ {\theta }$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$ {\alpha }$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$ {\beta }$ </tex-math></inline-formula> band ASP was observed with open eyes. Furthermore, open-eyed trials generally yielded a greater number of significant ASP differences across all bands during both adaptation and habituation, suggesting that following cortical activity during postural perturbation may be up-regulated with the availability of visual feedback. These results altogether provide deeper insight into pathological postural control failure by exploring the dynamic changes in both cortical activity and postural kinematics during adaptation and habituation to proprioceptive postural perturbation.
Cosmetic-Aware Makeup Cleanser

Face verification aims at determining whether a pair of face images belongs to the same identity. Recent studies have revealed the negative impact of facial makeup on the verification performance. With the rapid development of deep generative models, this paper proposes a semanticaware makeup cleanser (SAMC) to remove facial makeup under different poses and expressions and achieve verification via generation. The intuition lies in the fact that makeup is a combined effect of multiple cosmetics and tailored treatments should be imposed on different cosmetic regions. To this end, we present both unsupervised and supervised semantic-aware learning strategies in SAMC. At image level, an unsupervised attention module is jointly learned with the generator to locate cosmetic regions and estimate the degree. At feature level, we resort to the effort of face parsing merely in training phase and design a localized texture loss to serve complements and pursue superior synthetic quality. The experimental results on four makeuprelated datasets verify that SAMC not only produces appealing de-makeup outputs at a resolution of 256*256, but also facilitates makeup-invariant face verification through image generation.
Prevalence and knowledge of Salmonella infections among food handlers: Implications for school health in Southwestern Nigeria

Background: Food handlers play important roles in transmission of Salmonella infections in unregulated school food programs, most especially in settings where surveillance of foodborne disease is not routine. This study assessed the determinants and prevalence of Salmonella infections among food handlers and its implications for public school health in Southwestern Nigeria. Materials and Methods: A cross-sectional descriptive study among 526 food handlers was carried out using semi-structured interviewer-administered questionnaires. Stool collection and laboratory procedures were carried out under standard techniques. The SPSS software version 17.0 was used in data analysis. Frequency tables and charts were generated while binary logistic regression was used to demonstrate predictors of Salmonella infections, and P ≤ 0.05 was considered statistically significant. Results: The mean age of the respondents was 33.0 ± 7.6 years, 504 (95.8%) were females, and 378 (71.9%) were in the lowest socioeconomic class. Two hundred and seventy-seven (52.7%) had poor, 101 (19.2%) had moderate, while 148 (28.1%) had good knowledge scores as regards transmission, prevention, and control of Salmonella infections. Twenty-two (4.2%) had positive, 18 (3.4%) had indeterminate, while 486 (92.4%) had negative test results to Salmonella infections. Predictors of positive test results were being in the lower socioeconomic class, being a female and using pit toilets. Conclusion: Food handlers studied had significant prevalence rate and poor knowledge of Salmonella infections. Improving their knowledge could bring about a positive behavioral change toward a successful school feeding program.
Phytochemical screening and antioxidant activity of hemi-parasitic Indian mistletoe Viscum nepalense Sprengel

Viscum nepalense Sprengl hemi-parasitic mistletoe grown on Cassia fistula L. was collected from Bandipur National Park, Karnataka, India and investigated for its phytochem. constituents in different solvent exts. Results of the preliminary phytochem. anal. revealed the presence of alkaloids, flavanoids, tannins, saponins, sterols, cardiac glycosides, reducing compds. and absence of anthraquinones and tri-terpenes. Total phenolics (Folin-Ciocalteau method), antioxidant activity [DPPH(1,1-diphenyl-2-picrylhydrazyl) method] and reducing power assay of methanolic plant ext. differed according to the concn. and it was found that the above mentioned activities showed a concn. dependent increase.
Quantifying the effects of spatial resolution and noise on galaxy metallicity gradients

Metallicity gradients are important diagnostics of galaxy evolution, because they record the history of events such as mergers, gas inflow, and star formation. However, the accuracy with which gradients can be measured is limited by spatial resolution and noise, and hence, measurements need to be corrected for such effects. We use high-resolution (∼20 pc) simulation of a face-on Milky Way mass galaxy, coupled with photoionization models, to produce a suite of synthetic high-resolution integral field spectroscopy (IFS) datacubes. We then degrade the datacubes, with a range of realistic models for spatial resolution (2−16 beams per galaxy scale length) and noise, to investigate and quantify how well the input metallicity gradient can be recovered as a function of resolution and signal-to-noise ratio (SNR) with the intention to compare with modern IFS surveys like MaNGA and SAMI. Given appropriate propagation of uncertainties and pruning of low SNR pixels, we show that a resolution of 3–4 telescope beams per galaxy scale length is sufficient to recover the gradient to ∼10–20 per cent uncertainty. The uncertainty escalates to ∼60 per cent for lower resolution. Inclusion of the low SNR pixels causes the uncertainty in the inferred gradient to deteriorate. Our results can potentially inform future IFS surveys regarding the resolution and SNR required to achieve a desired accuracy in metallicity gradient measurements.
BReG-NeXt: Facial Affect Computing Using Adaptive Residual Networks With Bounded Gradient

This article introduces BReG-NeXt, a residual-based network architecture using a function wtih bounded derivative instead of a simple shortcut path (a.k.a. identity mapping) in the residual units for automatic recognition of facial expressions based on the categorical and dimensional models of affect. Compared to ResNet, our proposed adaptive complex mapping results in a shallower network with less numbers of training parameters and floating point operations per second (FLOPs). Adding trainable parameters to the bypass function further improves fitting and training the network and hence recognizing subtle facial expressions such as contempt with a higher accuracy. We conducted comprehensive experiments on the categorical and dimensional models of affect on the challenging in-the-wild databases of AffectNet, FER2013, and Affect-in-Wild. Our experimental results show that our adaptive complex mapping approach outperforms the original ResNet consisting of a simple identity mapping as well as other state-of-the-art methods for Facial Expression Recognition (FER). Various metrics are reported in both affect models to provide a comprehensive evaluation of our method. In the categorical model, BReG-NeXt-50 with only 3.1M training parameters and 15 MFLOPs, achieves 68.50 and 71.53 percent accuracy on AffectNet and FER2013 databases, respectively. In the dimensional model, BReG-NeXt achieves 0.2577 and 0.2882 RMSE value on AffectNet and Affect-in-Wild databases, respectively.
BanFakeNews: A Dataset for Detecting Fake News in Bangla

Observing the damages that can be done by the rapid propagation of fake news in various sectors like politics and finance, automatic identification of fake news using linguistic analysis has drawn the attention of the research community. However, such methods are largely being developed for English where low resource languages remain out of the focus. But the risks spawned by fake and manipulative news are not confined by languages. In this work, we propose an annotated dataset of ≈ 50K news that can be used for building automated fake news detection systems for a low resource language like Bangla. Additionally, we provide an analysis of the dataset and develop a benchmark system with state of the art NLP techniques to identify Bangla fake news. To create this system, we explore traditional linguistic features and neural network based methods. We expect this dataset will be a valuable resource for building technologies to prevent the spreading of fake news and contribute in research with low resource languages. The dataset and source code are publicly available at https://github.com/Rowan1697/FakeNews.
MER-GCN: Micro-Expression Recognition Based on Relation Modeling with Graph Convolutional Networks

Micro-Expression (ME) is the spontaneous, involuntary movement of a face that can reveal the true feeling. Recently, increasing researches have paid attention to this field combing deep learning techniques. Action units (AUs) are the fundamental actions reflecting the facial muscle movements and AU detection has been adopted by many researches to classify facial expressions. However, the time-consuming annotation process makes it difficult to correlate the combinations of AUs to specific emotion classes. Inspired by the nodes relationship building Graph Convolutional Networks (GCN), we propose an end-to-end AU-oriented graph classification network, namely MER-GCN, which uses 3D ConvNets to extract AU features and applies GCN layers to discover the dependency laying between AU nodes for ME categorization. To our best knowl-edge, this work is the first end-to-end architecture for Micro-Expression Recognition (MER) using AUs based GCN. The experimental results show that our approach outperforms CNN-based MER networks.
Carotid Plaque and Intima-Media Thickness Assessed by B-Mode Ultrasonography in Subjects Ranging From Young Adults to Centenarians

Background and Purpose—To investigate relationships among plaque formation, increasing intima-media thickness, and age, we examined ultrasonographically carotid arteries of subjects who had no major atherosclerotic risk factors and who ranged in age from young adults to centenarians. Methods—We studied 319 healthy subjects (154 men, 165 women; age range, 21 to 105 years) with no history of hypertension, diabetes mellitus, or atherosclerotic disease. Mean intima-media wall thickness (IMT) of common carotid arteries at plaque-free sites and prevalence of plaques were evaluated by B-mode ultrasound. Results—Mean common carotid IMT increased in a linear manner with age for all decades of life, including centenarians [IMT=(0.009×Age)+0.116] (r=0.83). In centenarians (n=30), intima-media complexes were diffusely thickened (mean IMT, 1.01 mm). Plaque prevalence increased up to the tenth decade of life (83.3%, n=30) but decreased in centenarians (60.0%). IMT and plaque prevalence were closely associated in the se.
Non-linear interlinkages and key objectives amongst the Paris Agreement and the Sustainable Development Goals

The United Nations' ambitions to combat climate change and prosper human development are manifested in the Paris Agreement and the Sustainable Development Goals (SDGs), respectively. These are inherently inter-linked as progress towards some of these objectives may accelerate or hinder progress towards others. We investigate how these two agendas influence each other by defining networks of 18 nodes, consisting of the 17 SDGs and climate change, for various groupings of countries. We compute a non-linear measure of conditional dependence, the partial distance correlation, given any subset of the remaining 16 variables. These correlations are treated as weights on edges, and weighted eigenvector centralities are calculated to determine the most important nodes. We find that SDG 6, clean water and sanitation, and SDG 4, quality education, are most central across nearly all groupings of countries. In developing regions, SDG 17, partnerships for the goals, is strongly connected to the progress of other objectives in the two agendas whilst, somewhat surprisingly, SDG 8, decent work and economic growth, is not as important in terms of eigenvector centrality.
The Origin and Evolution of Lyα Blobs in Cosmological Galaxy Formation Simulations

High-redshift Lyα blobs (LABs) are an enigmatic class of objects that have been the subject of numerous observational and theoretical investigations. It is of particular interest to determine the dominant power sources for their luminosity, as direct emission from H ii regions, cooling gas, and fluorescence due to the presence of active galactic nuclei (AGNs) can all contribute significantly. In this paper, we present the first theoretical model to consider all of these physical processes in an attempt to develop a model for the origin of LABs. This is achieved by combining a series of high-resolution cosmological zoom-in simulations with ionization and Lyα radiative transfer models. We find that massive galaxies display a range of Lyα luminosities and spatial extents (which strongly depend on the limiting surface brightness used) over the course of their lives, though regularly exhibit luminosities and sizes consistent with observed LABs. The model LABs are typically powered from a combination of recombination in star-forming galaxies, as well as cooling emission from gas associated with accretion. When AGNs are included in the model, the fluorescence caused by active galactic nucleus-driven ionization can be a significant contributor to the total Lyα luminosity as well. Within our modeled mass range, there are no obvious threshold physical properties that predict the appearance of LABs, and only weak correlations of the luminosity with the physical properties of the host galaxy. This is because the emergent Lyα luminosity from a system is a complex function of the gas temperature, ionization state, and Lyα escape fraction.
The Impact of Birth Order on Behavior in Contact Team Sports: the Evidence of Rugby Teams in Argentina

Several studies have shown that birth order and the sex of siblings may have an influence on individual behavioral traits. In particular, it has been found that second brothers (of older male siblings) tend to have more disciplinary problems. If this is the case, this should also be shown in contact sports. To assess this hypothesis we use a data set from the South Rugby Union (URS) from Bah\'ia Blanca, Argentina, and information obtained by surveying more than four hundred players of that league. We find a statistically significant positive relation between being a second-born male rugby player with an older male brother and the number of yellow cards received. \textbf{Keywords:} Birth Order; Behavior; Contact Sports; Rugby.
$\displaystyle \delta$-Primary Elements In Lattice Modules

In this paper, we introduce the expansion function δ on an L-module M . We define and investigate a δ-primary element in an L-module M . Its characterizations and many of its properties are obtained. δ0-primary and δ1-primary elements of an L-module M are related with 2-absorbing, 2-absorbing primary elements of an L-module M to obtain their special properties. The element δ1(N) ∈ M is related to rad(N) ∈ M , the radical element of M to obtain its properties where N ∈ M . We define a δL-primary element in an L-module M where δL is an expansion function on L and find relation among a δL-primary element of M and its corresponding δL-primary element of L. 2010 Mathematics Subject Classification: 06D10, 06E10, 06F10