Miracle-dz/UniFAR-FTUs huggingface dataset:
Co-Clustering on Bipartite Graphs for Robust Model Fitting

Recently, graph-based methods have been widely applied to model fitting. However, in these methods, association information is invariably lost when data points and model hypotheses are mapped to the graph domain. In this paper, we propose a novel model fitting method based on co-clustering on bipartite graphs (CBG) to estimate multiple model instances in data contaminated with outliers and noise. Model fitting is reformulated as a bipartite graph partition behavior. Specifically, we use a bipartite graph reduction technique to eliminate some insignificant vertices (outliers and invalid model hypotheses), thereby improving the reliability of the constructed bipartite graph and reducing the computational complexity. We then use a co-clustering algorithm to learn a structured optimal bipartite graph with exact connected components for partitioning that can directly estimate the model instances (i.e., post-processing steps are not required). The proposed method fully utilizes the duality of data points and model hypotheses on bipartite graphs, leading to superior fitting performance. Exhaustive experiments show that the proposed CBG method performs favorably when compared with several state-of-the-art fitting methods.
Remind Me, My Memory Is All Shook Up

Our brains synthesize vast and varied sensory inputs to represent an event or place that can later be recalled freely. The term “ engram ” refers to a group of neurons activated in association with a memory or event, suggesting that if one were to activate a subset of cells in the ensemble, one would trigger the recall of a memory. The medial temporal lobes, including the hippocampus, are often studied as the primary region of spatial engram formation and Tonegawa, 2020). However, newly formed spatial memory representations are incredibly transient.
SPECTROSCOPIC CONFIRMATION OF A z = 6.740 GALAXY BEHIND THE BULLET CLUSTER

We present the first results of our spectroscopic follow-up of 6.5 < z < 10 candidate galaxies behind clusters of galaxies. We report the spectroscopic confirmation of an intrinsically faint Lyman break galaxy (LBG) identified as a z850LP-band dropout behind the Bullet Cluster. We detect an emission line at λ = 9412 Å at >5σ significance using a 16 hr long exposure with FORS2 VLT. Based on the absence of flux in bluer broadband filters, the blue color of the source, and the absence of additional lines, we identify the line as Lyα at z = 6.740 ± 0.003. The integrated line flux is f = (0.7 ± 0.1 ± 0.3) × 10−17 erg−1 s−1 cm−2 (the uncertainties are due to random and flux calibration errors, respectively) making it the faintest Lyα flux detected at these redshifts. Given the magnification of μ = 3.0 ± 0.2 the intrinsic (corrected for lensing) flux is fint = (0.23 ± 0.03 ± 0.10 ± 0.02) × 10−17 erg−1 s−1 cm−2 (additional uncertainty due to magnification), which is ∼2–3 times fainter than other such measurements in z ∼ 7 galaxies. The intrinsic H160W-band magnitude of the object is , corresponding to 0.5 L* for LBGs at these redshifts. The galaxy is one of the two sub-L* LBG galaxies spectroscopically confirmed at these high redshifts (the other is also a lensed z = 7.045 galaxy), making it a valuable probe for the neutral hydrogen fraction in the early universe.
Influence of quantum energy equation on electronic plasma oscillations

Five-moment approximation in hydrodynamics includes not only continuity equation and momentum balance equation, but also energy equation. Set of hydrodynamic equations is presented for system of non-relativistic quantum particles with Coulomb interaction. This set of equations is linearized, and dispersion relation for Langmuir waves in quasi-neutral system of electrons and immobile ions is obtained.
Nabais Sa‐de Vries syndrome in a Chinese infant associated with a novel SPOP mutation: A clinical study and genetic report

Nabais Sa‐de Vries syndrome (NSDVS) is a newly identified neurodevelopmental disorder (NDD), characterized by mutations in the SPOP gene, which encodes the speckle‐type BTB/POZ protein. It is divided into two disease subtypes, according to patient facial features, which could be related to altered SPOP protein function. Few studies have documented this syndrome and little is known about its pathophysiology. Herein, we present an unexplained infant case of NDD, possibly the first Asian NSDVS case report.
Development of venetoclax performance using its new derivatives on BCL‐2 protein inhibition

Cancer cells are resistant to apoptosis and this is one of the most obvious symptoms of cancer in humans. One of the most exciting strategies for treating cancer is to design regulators that increase cell death and stop cell growth. Members of the BCL‐2 family of proteins play an important role in the regulation of apoptosis. In this study, an attempt was made to improve the performance of one of the anticancer drugs by designing new analogs of venetoclax (VNT). For this purpose, molecular docking studies were performed to determine the best binding state of VNT and its newly designed derivatives at the protein‐binding site to estimate the binding energy. The best analog in terms of free energy was VNT‐12 with the lowest energy (−12.15 kcal/mol). Finally, to investigate the inhibitory effect of the compounds on BCL‐2 protein, molecular dynamics simulation was used, and by performing the relevant analyses during the simulation, it was observed that the newly designed ligand had better performance in inhibiting BCL‐2 protein compared to VNT.
Wild Low-Dimensional Topology and Dynamics

Wild Low-Dimensional Topology and Dynamics Mark Hansen Meilstrup Department of Mathematics Doctor of Philosophy In this dissertation we discuss various results for spaces that are wild, i.e. not locally simply connected. We first discuss periodic properties of maps from a given space to itself, similar to Sharkovskĭı’s Theorem for interval maps. We study many non-locally connected spaces and show that some have periodic structure either identical or related to Sharkovskĭı’s result, while others have essentially no restrictions on the periodic structure. We next consider embeddings of solenoids together with their complements in three space. We differentiate solenoid complements via both algebraic and geometric means, and show that every solenoid has an unknotted embedding with Abelian fundamental group, as well as infinitely many inequivalent knotted embeddings with non-Abelian fundamental group. We end by discussing Peano continua, particularly considering subsets where the space is or is not locally simply connected. We present reduced forms for homotopy types of Peano continua, and provide a few applications of these results.
Nano-read-across predictions of toxicity of metal oxide engineered nanoparticles (MeOx ENPS) used in nanopesticides to BEAS-2B and RAW 264.7 cells

Abstract The demand for nutrients and new technologies has increased with population growth. The agro-technological revolution with metal oxide engineered nanoparticles (MeOx ENPs) has the potential to reform the resilient agricultural system while maintaining the security of food. When utilized extensively, MeOx ENPs may have unintended toxicological effects on both target and non-targeted species. Since limited information about nanopesticides’ pernicious effects is available, in silico modeling can be done to explore these issues. Hence, in the present work, we have applied computational modeling to explore the influence of metal oxide nanoparticles on the toxicity of bronchial epithelial (BEAS-2B) and murine myeloid (RAW 264.7) cells to bridge the data gap relating to the toxicity of MeOx NPs. Initially, partial least squares (PLS) regression models were developed applying the Small Dataset Modeler software (http://teqip.jdvu.ac.in/QSAR_Tools/DTCLab/) using four datasets having effective concentration (EC50%) as the endpoints and employing only periodic table descriptors. To further explore the predictions, we applied a read-across approach using the descriptors selected in the QSAR models. Also, the inter-endpoint cytotoxicity relationship modeling (quantitative toxicity-toxicity relationship or QTTR) was conducted. It was found that the result obtained by nano-read-across provided a similar level of accuracy as provided by QSAR. The information derived from the PLS models of both the cell lines suggested that metal cation formation, and bond-forming capacity influence the toxicity whereas the presence of metal has an influential impact on the ecotoxicological effects. Thus, it is feasible to design safe nanopesticides that could be more effective than conventional analogs. Graphical Abstract
Deep Learning-Based Detection of Epileptiform Discharges for Self-Limited Epilepsy With Centrotemporal Spikes

Centrotemporal spike-waves (CTSWs) are typical interictal epileptiform discharges (IEDs) observed in centrotemporal regions in self-limited epilepsy with centrotemporal spikes (SLECTS). This study aims to develop a deep learning-based approach for automated detection of CTSWs in scalp electroencephalography (EEG) recordings of patients with SLECTS. To lower the substantial burden of IED annotation on clinicians, we simplified it by limiting IEDs to CTSWs because electroencephalographic patterns of CTSWs are known to be highly consistent. Two neurologists annotated 1672 CTSWs of 20 patients with SLECTS. Thereafter, we performed a two-level CTSW detection procedure: epoch-level and EEG-level. In the epoch-level detection, we constructed convolutional neural network-based classification models for CTSW and non-CTSW binary classification using the recordings of 20 patients and 20 controls. We then set the thresholds of the classification models for 100% specificity. In the EEG-level detection, we applied the threshold-adjusted classification models to the recordings of 50 patients and 50 controls that were not used in the epoch-level detection to distinguish between CTSW-positive (with one or more CTSWs) and CTSW-negative (with no CTSW) recordings based on the detection of CTSW presence. We obtained an average sensitivity, specificity, and accuracy of 99.8%, 98.4%, and 99.1%, respectively, with an average false detection rate of 0.19/hr for the controls. Our approach showed high detectability for CTSWs despite the simplified annotation process. We expect that the proposed CTSW detectors have potential clinical usefulness for efficiently reading EEGs and diagnosing SLECTS, and can significantly reduce the burden of IED annotation on clinicians.
BIMA Sub-arcsecond Carbon Monoxide Observations: Resolving the Inner kpc Region of the QSO I Zw 1

We present the first sub-kpc (rv O. 7" ~ 0.8 kpc) resolution 12CO(I-0) observations of the ISM in the host galaxy of the QSO I Zw 1 which were obtained with the BIMA rum-interferometer in its A configuration. The measurements, which are part of a multi-wavelength study of I Zw 1, will allow comparison of the ISM properties of a QSO host with those of nearby galaxies and place constraints on galaxy forma-tion/evolution models. Our maps of the 12CO(I-0) line emission from the host galaxy of a QSO show a ring-like structure in the circumnuclear molecular gas distribution with a radius of about 900 pc. The presence of such a molecular gas ring was already predicted from earlier lower angular resolution PdBI observations (Schinnerer, Eckart, & Tacconi 1998). A first comparison of the BIMA data with new PdBI 12CO(2-1) observations with 0.9" angular resolution shows variations in the excitation conditions of the molecular gas in the innermost 3" comprising the nuclear region of I Zw 1.
Heterogeneity of T cells and macrophages in chlorine-induced acute lung injury in mice using single-cell RNA sequencing

Abstract Objective Chlorine (Cl2), as an asphyxiant toxicant, induced poisoning incidents and acute lung injury (ALI) occur frequently. The specific pathogenesis of Cl2-induced ALI remains unclear. Immune cells play an important role in the process of lung damage. We used single-cell RNA sequencing (scRNA-seq) technology to explore T cells and macrophages molecular mechanism. Methods Female BALB/c mice were exposed to 400 ppm Cl2 for 15 min. scRNA-seq technology was used to observe the heterogeneity of T cells and macrophages. Hematoxylin–eosin (H&E) staining was used to evaluate the degree of lung injury. Immunofluorescence was used to verify the highly expressed genes of our interest. Results A total of 5316 to 7742 cells were classified into eight different cell types. Several new highly expressed anti-inflammatory and pro-inflammatory genes were found in T cells and macrophages, which were further verified in vitro. Through the pseudotime analysis of macrophages, it was found that the expression of pro-inflammatory and anti-inflammatory genes showed opposite trends in the development of Cl2-induced ALI. This study also mapped T cells-macrophage communication and identified the development of several important receptor-ligand complexes in Cl2-induced ALI. Conclusions These findings are worthy of further exploration and provide new resources and directions for the study of Cl2-induced ALI in mice, especially in immune and inflammation mechanisms.
Cardiac-derived extracellular matrix: A decellularization protocol for heart regeneration

Extracellular matrix (ECM) is a fundamental component of the heart, guiding vital cellular processes during organ homeostasis. Most cardiovascular diseases lead to a remarkable remodeling of the ECM, accompanied by the formation of a fibrotic tissue that heavily compromises the heart function. Effective therapies for managing fibrosis and promoting physiological ECM repair are not yet available. The production of a decellularized extracellular matrix (d-ECM) serving as a three-dimensional and bioactive scaffold able to modulate cellular behavior and activities is considered crucial to achieve a successful regeneration. The protocol represents a step-by-step method to obtain a decellularized cardiac matrix through the combination of sodium dodecyl sulphate (SDS) and Triton X-100. Briefly, cardiac samples obtained from left ventricles of explanted, pathological human hearts were dissected and washed to remove residual body fluids. Samples were then snap-frozen and sliced by a cryostat into 350 μm thick sections. The sections obtained were decellularized using a solution containing 1% Triton X-100 and 1% SDS in combination, for 24 hours, until observing the color change from brownish-red to translucent-white. As a result, the protocol shows efficiency in preserving ECM architecture and protein composition during the whole process, suggesting that it is worthwhile, highly reproducible and produces a well- preserved decellularized extracellular matrix from cardiac samples. Notwithstanding, some limitations need to be addressed, such as the risk for microbial contamination and the unpredictable trend of the protocol when applied to decellularize samples other than myocardium, vessels, or skin. These issues require antibiotics mixture supplement during the procedure followed by UV sterilization, and appropriate adjustments for a tissue-specific utilization, respectively. The protocol is intended to produce a cardiac d-ECM for cell settlement, representing the ideal scaffold for tissue engineering purposes.
Reflect on emotional events from an observer’s perspective: a meta-analysis of experimental studies

ABSTRACT Self-distancing has been proposed as an emotion regulation strategy to reduce the duration and intensity of emotions. This meta-analysis synthesised 48 studies and 102 effect sizes examining the effects of self-distancing on emotion regulation. The results showed an overall significant, small effect of self-distancing in attenuating emotional responses (Hedges’ g = −0.26, 95%CI: [−0.36, −0.15]). Moderator analyses highlighted the efficacy of one intervention feature: approach. Stronger effect was associated with the visual and verbal approach to process emotional events, in comparison to the visual only approach and the pronouns approach. The effectiveness of self-distancing was consistent across other intervention features (context, stimuli, time, emotional outcome) and individual characteristics (emotional vulnerability, age, culture). These findings suggest that self-distancing is effective in emotion regulation when people externalise and articulate thoughts through writing and talking. Practical implications were discussed in relation to the design of interventions to enhance emotional well-being.
Social reward anticipation in infants as revealed by event-related potentials

ABSTRACT Infants engage in gaze interaction from the early stage of life. Emerging studies suggest that infants may expect social reward of shared attention before looking to the same object with another person. However, it was unknown about the neural responses during the anticipation of social rewards before shared attention in infants. We tested infants’ reward anticipations in the gaze cueing situation measured by event-related potentials in the social association learning task. Six- to ten-month-old infants (N = 20) repeatedly observed that a female predictively looked toward the animation position (valid condition) or another female looking away from the animation (invalid condition). It was posited that infants could learn associations between female faces and the event of shared attention. The results showed that the stimulus preceding negativity which reflects reward anticipation before the animation presentation was elicited in the second half of the learning phases in the valid condition. Additionally, after the presentation of the face, N290 was greater in the second half of the learning phase than in the first half in the valid condition. These results suggest that infants can anticipate social reward from gaze cues, and learning the gaze cueing validity may affect not only reward anticipation but face perception.
Fluid-Structure Interaction Within Models of Patient-Specific Arteries: Computational Simulations and Experimental Validations

Cardiovascular disease (CVD) is the leading cause of mortality worldwide and its incidence is rising due to an aging population. The development and progression of CVD is directly linked to adverse vascular hemodynamics and biomechanics, whose in-vivo measurement remains challenging but can be simulated numerically and experimentally. The ability to evaluate these parameters in patient-specific CVD cases is crucial to better predict future disease progression, risk of adverse events, and treatment efficacy. While significant progress has been made toward patient-specific hemodynamic simulations, blood vessels are often assumed to be rigid, which does not consider the compliant mechanical properties of vessels whose malfunction is implicated in disease. In an effort to simulate the biomechanics of flexible vessels, fluid-structure interaction (FSI) simulations have emerged as promising tools for the characterization of hemodynamics within patient-specific cardiovascular anatomies. Since FSI simulations combine the blood's fluid domain with the arterial structural domain, they pose novel challenges for their experimental validation. This paper reviews the scientific work related to FSI simulations for patient-specific arterial geometries and the current standard of FSI model validation including the use of compliant arterial phantoms, which offer novel potential for the experimental validation of FSI results.
Identification de signaux multicomposantes à phase polynomiale et à amplitude variable

La fonction d'ambiguïté d'ordre supérieur (HAF highorder ambiguïty function [8]), introduite par Peleg [7, 5, 6] sous le nom de transformée polynomiale de phase (TPP), est particulièrement bien adaptée à l'estimation des paramètres des signaux à phase polynomiale. Nous présentons ici une extension de cette méthode aux signaux à amplitude variable. Nous proposons d'utiliser, pour estimer ces amplitudes, des ltres de Kalman linéaires et non stationnaires. On présente des résultats obtenus en simulation et sur des signaux réels de test d'enceintes acoustiques.
OntoPopulis, a System for Learning Semantic Classes

Ontopopulis is a multilingual weakly supervised terminology learning algorithm which takes on its input a set of seed terms for a semantic category and an unannotated text corpus. The algorithm learns additional terms, which belong to this category. For example, for the category “environmental disasters” the input seed set in English is environmental disaster, water pollution, climate change. Among the highest ranked new terms which the system learns for this semantic class are deforestation, global warming and so on.
Ontology of Visual Objects

The focus of the paper is the Ontology of Visual Objects based on WordNet noun hierarchies. In particular, we present a methodology for bidirectional ontology engineering, which integrates the pre-existing knowledge resources and the selection of visual objects within the images representing particular thematic domains. The Ontology of Visual Objects organizes concepts labeled by corresponding classes (dominant classes, classes that are attributes to dominant classes, and classes that serve only as parents to dominant classes), relations between concepts and axioms defining the properties of the relations. The Ontology contains 851 classes (706 dominant and attribute classes), 15 relations and a number of axioms built upon them. The definition of relations between dominant and attribute classes and formulations of axioms based on the properties of the relations offers a reliable means for automatic object or image classification and description.
Syntactic characteristics of emotive predicates in Bulgarian: A corpus-based study

The paper presents a corpus-based study of emotive predicates (verbs and predicative constructions with adjectival, adverbial or noun phrases) in Bulgarian with respect to their syntactic characteristics. The sources of empirical data analyzed here are Bulgarian National Corpus, Corpus of Bulgarian Political and Journalistic Speech and Bulgarian part of Multilingual Comparable Corpora of Parliamentary Debates ParlaMint. The analyzes are organized in terms of morpho-syntactic features of emotive predicates, transitivity, syntactic functions and theta-roles of their arguments. Emotive predicates denote a state or an event involving an affective experience. As part of the special semantic class of psychological/Experiencer verbs, they have been studied in relation to the interaction between lexical semantics and argument realization. Bulgarian data confirm the well-established division of Psych predicates into three classes: Subject Experiencer (fear type verbs), Object Experiencer (frighten type verbs), Dative Experiencer. The third class is mostly represented by adverbial predicates.
Second Phase Dissolution and Grain Characteristics of As-Cast Al-Cu-Li Alloys with Different Mg Contents during Homogenization

Homogenization treatment is usually indispensable to obtain a good microstructure pattern and brilliant final performance of Al-Cu-Li alloys. In the present study, the effect of different Mg contents on the microstructure of Al-Cu-Li alloys during homogenization was investigated utilizing optical microscopy (OM), scanning electron microscope (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD) and differential scanning calorimetry (DSC) analysis. The results indicated that the higher Mg content changed the type of grain boundary phase in the as-cast alloy. The eutectic phases in the low Mg alloy were dominated by Cu-rich phases while the high Mg alloy also had many Ag-containing Al2CuMg phases. The difference in Mg contents did not affect the grain morphology, while the high Mg content in the Cu-rich phase caused a decrease in its melting point. Suitable homogenization treatments for the low and high Mg alloys are 520 °C/12 h and 495 °C/24h + 505 °C/48 h, respectively. This provides a reference for studies related to the effect of composition evolution on the dissolution of the second phase during the homogenization treatment.