Miracle-dz/UniFAR-FTUs huggingface dataset:
A study of an expanding interplanetary magnetic cloud and its interaction with the Earth's magnetosphere: The interplanetary aspect

In a series of three interlinked papers we present a study of an interplanetary magnetic cloud and its interaction with the Earth's magnetosphere on January 14/15, 1988. This first paper is divided into three parts describing the principal results concerning the magnetic cloud. First, by applying the cylindrically symmetric, magnetic flux rope model to the high time resolution magnetic field and plasma data obtained by the IMP-8 spacecraft, we show that the axis of the magnetic cloud in question is approximately in the ecliptic and orthogonal to the Earth-Sun line. We note the presence of pulsations of ∼5-hour period in the bulk flow speed which are superimposed on an otherwise monotonically falling bulk speed profile. Second, we apply ideal MHD to model the self-similar, radial expansion of a magnetic cloud of cylindrical geometry. As initial condition for the magnetic field we choose a constant-α, force-free magnetic configuration. We demonstrate that the theoretical velocity profile for the free expansion of a magnetic cloud is consistent with observations made during the January 14/15, 1988, magnetic cloud encounter. Comparing model with data, we infer that prior to the start of observations at 1 AU the magnetic cloud had been expanding for 65.4 hours; the radius of the magnetic cloud at the time it arrived at Earth was 0.18 AU; and its expansion speed at 1 AU was ∼114 km/s. Third, we discuss energetic (∼1 MeV) ion data, also from instrumentation on IMP-8. We highlight the appearance of a sharp enhancement in the intensity of ∼0.5-MeV ions while IMP-8 was inside the cloud. These ions travel as a collimated, field-aligned beam from the west of the Sun. This is an “impulsive” solar event in which particles accelerated at a magnetically well-connected solar flare arrive promptly at the spacecraft. The observation of solar flare particles inside the cloud suggests that field lines within the magnetic cloud remained connected to the Sun. The observation is, however, inconsistent with the supposition that the cloud is formed of closed magnetic field loops disconnected from the Sun.
Process Mining meets Statistical Model Checking to Explain Threat Models: Novel Approach to Model Validation and Enhancement (Extended Abstract)

Formal verification of the dynamics of a system can be conducted by employing statistical analysis techniques, such as Statistical Model Checking (SMC). SMC techniques resort to probabilistic simulations to evaluate the system properties to help to circumvent the state space explosion problem, the well-known curse of the classic model checking techniques. Nevertheless, SMC provides only estimations and confidence intervals of the evaluated properties of the system without explaining why the analysis estimated a particular property value. This project aims to present a novel methodology that integrates SMC with process-oriented data-driven techniques known as process mining (PM) applied to threat models. This methodology will empower modelers to see their models’ unfolded behavior instead of just numerical aggregated values obtained by SMC analysis. In the present work, there are two research goals. The primary research goal focus on implementing and validating the novel methodology in which we enrich SMC techniques with PM techniques. The secondary research goals focus on implementing an approach to extract an attack pattern from its textual description and another to extract a textual description of the salient information from the process model discovered using PM techniques. The secondary research goals add the necessary means to assist a modeler in using this novel methodology.
Evaluation of Data Augmentation for Named Entity Recognition in the German Legal Domain

One of the techniques to solve Natural Language Processing tasks is supervised learning, which requires large labeled datasets for model training. Such datasets are usually unavailable for specific domains or languages other than English. Creating them manually is a time-consuming task. This paper aims to explore methods to artificially expand small datasets in the German legal domain. We tested three Data Augmentation approaches on differently sized fragments of the German Legal Entity Recognition dataset: Synonym replacement, mention replacement, and back translation. We evaluated the effect of training on the augmented data with a bidirectional Long Short-Term Memory Network with a Conditional Random Field layer and a Transformer-based model. It appears that synonym replacement and mention replacement yield similarly positive results, while the latter is less time-consuming. Performing back translation turns out as challenging using legal texts.
Sub-700fs pulses at 152 W average power from a Tm-doped fiber CPA system

Thulium-based fiber lasers potentially provide for the demand of high average-power ultrafast laser systems operating at an emission wavelength around 2 μm. In this work we use a Tm-doped photonic-crystal fiber (PCF) with a mode field diameter of 36 μm enabling high peak powers without the onset of detrimental nonlinear effects. For the first time a Tmdoped PCF amplifier allows for a pump-power limited average output power of 241 W with a slope efficiency above 50%, good beam quality and linear polarization. A record compressed average power of 152 W and a pulse peak power of more than 4 MW at sub-700 fs pulse duration are enabled by dielectric gratings with diffraction efficiencies higher than 98% leading to a total compression efficiency of more than 70%. A further increase of pulse peak power towards the GW-level is planned by employing Tm-doped large-pitch fibers with mode field diameters well above 50 μm. The coherent combination of ultrafast pulses might eventually lead to kW-level average power and multi-GW peak power.
M5 V101 - A close binary system in a globular cluster

Spectrophotometric and photographic observations of the large amplitude variable V101 in the globular cluster M5 show it to have the characteristics of a dwarf nova. In particular, a spectrum obtained with the Hale 5 m reflector of the object in quiescence (V approximately equal to 20) shows strong, broad Balmer and He I emission. It is suggested that M5 V101 is the strongest case for the existence of close binary systems in globular clusters.
CARMA3: A potential therapeutic target in non-cancer diseases

Caspase recruitment domain and membrane-associated guanylate kinase-like protein 3 (CARMA3) is a scaffold protein widely expressed in non-hematopoietic cells. It is encoded by the caspase recruitment domain protein 10 (CARD10) gene. CARMA3 can form a CARMA3-BCL10-MALT1 complex by recruiting B cell lymphoma 10 (BCL10) and mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1), thereby activating nuclear factor-κB (NF-κB), a key transcription factor that involves in various biological responses. CARMA3 mediates different receptors-dependent signaling pathways, including G protein-coupled receptors (GPCRs) and receptor tyrosine kinases (RTKs). Inappropriate expression and activation of GPCRs and/or RTKs/CARMA3 signaling lead to the pathogenesis of human diseases. Emerging studies have reported that CARMA3 mediates the development of various types of cancers. Moreover, CARMA3 and its partners participate in human non-cancer diseases, including atherogenesis, abdominal aortic aneurysm, asthma, pulmonary fibrosis, liver fibrosis, insulin resistance, inflammatory bowel disease, and psoriasis. Here we provide a review on its structure, regulation, and molecular function, and further highlight recent findings in human non-cancerous diseases, which will provide a novel therapeutic target.
Incorporating structural abnormalities in equivalent dipole layer based ECG simulations

Introduction: Electrical activity of the myocardium is recorded with the 12-lead ECG. ECG simulations can improve our understanding of the relation between abnormal ventricular activation in diseased myocardium and body surface potentials (BSP). However, in equivalent dipole layer (EDL)-based ECG simulations, the presence of diseased myocardium breaks the equivalence of the dipole layer. To simulate diseased myocardium, patches with altered electrophysiological characteristics were incorporated within the model. The relation between diseased myocardium and corresponding BSP was investigated in a simulation study. Methods: Activation sequences in normal and diseased myocardium were simulated and corresponding 64-lead BSP were computed in four models with distinct patch locations. QRS-complexes were compared using correlation coefficient (CC). The effect of different types of patch activation was assessed. Of one patient, simulated electrograms were compared to electrograms recorded during invasive electro-anatomical mapping. Results: Hundred-fifty-three abnormal activation sequences were simulated. Median QRS-CC of delayed versus dyssynchronous were significantly different (1.00 vs. 0.97, p < 0.001). Depending on the location of the patch, BSP leads were affected differently. Within diseased regions, fragmentation, low bipolar voltages and late potentials were observed in both recorded and simulated electrograms. Discussion: A novel method to simulate cardiomyopathy in EDL-based ECG simulations was established and evaluated. The new patch-based approach created a realistic relation between ECG waveforms and underlying activation sequences. Findings in the simulated cases were in agreement with clinical observations. With this method, our understanding of disease progression in cardiomyopathies may be further improved and used in advanced inverse ECG procedures.
Interpretable cardiac anatomy modeling using variational mesh autoencoders

Cardiac anatomy and function vary considerably across the human population with important implications for clinical diagnosis and treatment planning. Consequently, many computer-based approaches have been developed to capture this variability for a wide range of applications, including explainable cardiac disease detection and prediction, dimensionality reduction, cardiac shape analysis, and the generation of virtual heart populations. In this work, we propose a variational mesh autoencoder (mesh VAE) as a novel geometric deep learning approach to model such population-wide variations in cardiac shapes. It embeds multi-scale graph convolutions and mesh pooling layers in a hierarchical VAE framework to enable direct processing of surface mesh representations of the cardiac anatomy in an efficient manner. The proposed mesh VAE achieves low reconstruction errors on a dataset of 3D cardiac meshes from over 1,000 patients with acute myocardial infarction, with mean surface distances between input and reconstructed meshes below the underlying image resolution. We also find that it outperforms a voxelgrid-based deep learning benchmark in terms of both mean surface distance and Hausdorff distance while requiring considerably less memory. Furthermore, we explore the quality and interpretability of the mesh VAE's latent space and showcase its ability to improve the prediction of major adverse cardiac events over a clinical benchmark. Finally, we investigate the method's ability to generate realistic virtual populations of cardiac anatomies and find good alignment between the synthesized and gold standard mesh populations in terms of multiple clinical metrics.
Effects of acute ischemic stroke on binaural perception

Stroke-induced lesions at different locations in the brain can affect various aspects of binaural hearing, including spatial perception. Previous studies found impairments in binaural hearing, especially in patients with temporal lobe tumors or lesions, but also resulting from lesions all along the auditory pathway from brainstem nuclei up to the auditory cortex. Currently, structural magnetic resonance imaging (MRI) is used in the clinical treatment routine of stroke patients. In combination with structural imaging, an analysis of binaural hearing enables a better understanding of hearing-related signaling pathways and of clinical disorders of binaural processing after a stroke. However, little data are currently available on binaural hearing in stroke patients, particularly for the acute phase of stroke. Here, we sought to address this gap in an exploratory study of patients in the acute phase of ischemic stroke. We conducted psychoacoustic measurements using two tasks of binaural hearing: binaural tone-in-noise detection, and lateralization of stimuli with interaural time- or level differences. The location of the stroke lesion was established by previously acquired MRI data. An additional general assessment included three-frequency audiometry, cognitive assessments, and depression screening. Fifty-five patients participated in the experiments, on average 5 days after their stroke onset. Patients whose lesions were in different locations were tested, including lesions in brainstem areas, basal ganglia, thalamus, temporal lobe, and other cortical and subcortical areas. Lateralization impairments were found in most patients with lesions within the auditory pathway. Lesioned areas at brainstem levels led to distortions of lateralization in both hemifields, thalamus lesions were correlated with a shift of the whole auditory space, whereas some cortical lesions predominantly affected the lateralization of stimuli contralateral to the lesion and resulted in more variable responses. Lateralization performance was also found to be affected by lesions of the right, but not the left, basal ganglia, as well as by lesions in non-auditory cortical areas. In general, altered lateralization was common in the stroke group. In contrast, deficits in tone-in-noise detection were relatively scarce in our sample of lesion patients, although a significant number of patients with multiple lesion sites were not able to complete the task.
A test of the ecological valence theory of color preference, the case of Arabic

Humans have systematic and reliable color preferences. The dominant account of color preference is that individuals like some colors more than others due to the valence of objects that they associate with colors (Ecological Valence Theory). In support of this theory, Palmer and Schloss show that the average valence of objects associated with a color, when weighted (the WAVE), explains up to 80% of the variation in color preference for adults from the United States (US). Here we investigate whether Ecological Valence Theory can account for the color preferences of female and male adults from Saudi Arabia to test how well the theory generalizes across cultures and how well it accounts for sex differences in color preference. We also extend the investigation of EVT by investigating whether abstract concept associations as well as object associations can account for preference. Saudi adults’ color preferences, color object and concept associations, and association valence ratings were collected, and the WAVE was computed and correlated with preference ratings. The WAVE accounted for no more than half of the variance in Saudi color preferences, although there was some degree of sex specificity in the relationship of the WAVE and color preference. Adding abstract concept associations did not account for more variance than object associations alone, but the number of abstract concept associations did account for a significant amount of the variance in color preference for females, but not males. The findings converge with other cross-cultural studies in suggesting that the success of EVT in accounting for color preference varies across cultures and indicates that additional factors other than color associations are likely also at play.
How to alleviate cardiac injury from electric shocks at the cellular level

Electric shocks, the only effective therapy for ventricular fibrillation, also electroporate cardiac cells and contribute to the high-mortality post-cardiac arrest syndrome. Copolymers such as Poloxamer 188 (P188) are known to preserve the membrane integrity and viability of electroporated cells, but their utility against cardiac injury from cardiopulmonary resuscitation (CPR) remains to be established. We studied the time course of cell killing, mechanisms of cell death, and protection with P188 in AC16 human cardiomyocytes exposed to micro- or nanosecond pulsed electric field (μsPEF and nsPEF) shocks. A 3D printer was customized with an electrode holder to precisely position electrodes orthogonal to a cell monolayer in a nanofiber multiwell plate. Trains of nsPEF shocks (200, 300-ns pulses at 1.74 kV) or μsPEF shocks (20, 100-μs pulses at 300 V) produced a non-uniform electric field enabling efficient measurements of the lethal effect in a wide range of the electric field strength. Cell viability and caspase 3/7 expression were measured by fluorescent microscopy 2–24 h after the treatment. nsPEF shocks caused little or no caspase 3/7 activation; most of the lethally injured cells were permeable to propidium dye already at 2 h after the exposure. In contrast, μsPEF shocks caused strong activation of caspase 3/7 at 2 h and the number of dead cells grew up to 24 h, indicating the prevalence of the apoptotic death pathway. P188 at 0.2–1% reduced cell death, suggesting its potential utility in vivo to alleviate electric injury from defibrillation.
Transcriptomic analysis unravels the molecular response of Lonicera japonica leaves to chilling stress

Lonicera japonica is not only an important resource of traditional Chinese medicine, but also has very high horticultural value. Studies have been performed on the physiological responses of L. japonica leaves to chilling, however, the molecular mechanism underlying the low temperature-induced leaves morphological changes remains unclear. In this study, it has been demonstrated that the ratio of pigments content including anthocyanins, chlorophylls, and carotenoids was significantly altered in response to chilling condition, resulting in the color transformation of leaves from green to purple. Transcriptomic analysis showed there were 10,329 differentially expressed genes (DEGs) co-expressed during chilling stress. DEGs were mainly mapped to secondary metabolism, cell wall, and minor carbohydrate. The upregulated genes (UGs) were mainly enriched in protein metabolism, transport, and signaling, while UGs in secondary metabolism were mainly involved in phenylpropaoids-flavonoids pathway (PFP) and carotenoids pathway (CP). Protein-protein interaction analysis illustrated that 21 interacted genes including CAX3, NHX2, ACA8, and ACA9 were enriched in calcium transport/potassium ion transport. BR biosynthesis pathway related genes and BR insensitive (BRI) were collectively induced by chilling stress. Furthermore, the expression of genes involved in anthocyanins and CPs as well as the content of chlorogenic acid (CGA) and luteoloside were increased in leaves of L. japonica under stress. Taken together, these results indicate that the activation of PFP and CP in leaves of L. japonica under chilling stress, largely attributed to the elevation of calcium homeostasis and stimulation of BR signaling, which then regulated the PFP/CP related transcription factors.
Resilience and active inference

In this article, we aim to conceptualize and formalize the construct of resilience using the tools of active inference, a new physics-based modeling approach apt for the description and analysis of complex adaptive systems. We intend this as a first step toward a computational model of resilient systems. We begin by offering a conceptual analysis of resilience, to clarify its meaning, as established in the literature. We examine an orthogonal, threefold distinction between meanings of the word “resilience”: (i) inertia, or the ability to resist change (ii) elasticity, or the ability to bounce back from a perturbation, and (iii) plasticity, or the ability to flexibly expand the repertoire of adaptive states. We then situate all three senses of resilience within active inference. We map resilience as inertia onto high precision beliefs, resilience as elasticity onto relaxation back to characteristic (i.e., attracting) states, and resilience as plasticity onto functional redundancy and structural degeneracy.
Predictive value of novel inflammatory markers platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, and monocyte-to-lymphocyte ratio in arterial stiffness in patients with diabetes: A propensity score–matched analysis

Background Increased arterial stiffness is common in patients with diabetes, and inflammation is one of the main causes of increased arterial stiffness. Platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and monocyte-to-lymphocyte ratio (MLR) are novel inflammatory markers that are reproducible, widely available, and easy to measure, and are associated with low costs. This study sought to investigate the predictive value of these novel inflammatory markers in patients with diabetes having arterial stiffness. Methods We retrospectively included inpatients with diabetes mellitus from the Endocrinology Department of the Chengdu Fifth People’s Hospital from June 2021 to May 2022 and collected data on their general information, biochemical indicators, and brachial-ankle pulse wave velocity (baPWV). After propensity matching, the risk relationship between PLR, NLR, and MLR and arterial stiffness was assessed in the recruited patients. Results A total of 882 hospitalized patients with diabetes were included in this study and categorized into the low baPWV (507 cases) or high baPWV group (375 cases) based on the baPWV. After propensity matching, there were 180 patients in all in the high and low baPWV groups. Univariate and multivariate logistic regression analyses revealed that high PLR, NLR, and MLR were independently associated with an increased risk of arterial stiffness in patients with diabetes. In the receiver operating characteristic curve analysis, the NLR area under the curve (AUC) was 0.7194 (sensitivity = 84.4%, specificity = 51.1%) when distinguishing low baPWV and high baPWV in patients with diabetes, which was higher than that for PLR AUC (0.6477) and MLR AUC (0.6479), and the combined diagnosis for AUC. Conclusions NLR was superior to PLR, and MLR and combined diagnosis have certain predictive values that indicate the increase in arterial stiffness in patients with diabetes. These predictive values can help with the early identification of increased arterial stiffness in patients with diabetes.