Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthetic Data in Human Analysis: A Survey

Deep neural networks have become prevalent in human analysis, boosting the performance of applications, such as biometric recognition, action recognition, as well as person re-identification. However, the performance of such networks scales with the available training data. In human analysis, the demand for large-scale datasets poses a severe challenge, as data collection is tedious, time-expensive, costly and must comply with data protection laws. Current research investigates the generation of synthetic data as an efficient and privacy-ensuring alternative to collecting real data in the field. This survey introduces the basic definitions and methodologies, essential when generating and employing synthetic data for human analysis. We conduct a survey that summarises current state-of-the-art methods and the main benefits of using synthetic data. We also provide an overview of publicly available synthetic datasets and generation models. Finally, we discuss limitations, as well as open research problems in this field. This survey is intended for researchers and practitioners in the field of human analysis.
Simple time‐domain analysis of a multilevel DC–DC flying capacitor converter average aperiodic natural balancing dynamics

Reported capacitor average natural voltage balancing dynamics analysis methods are mostly based on frequency-domain Fourier transformations that involve infinite series. Therefore, these methods require high mathematical skills, are not truly analytical and difficult to use in engineering practise. This study suggests a time-domain power averaging-based approach to the analysis of a multilevel DC-DC flying capacitor converter (or, more generally, switched capacitive converter) aperiodic (non-oscillating) average voltage balancing dynamics. Simple analytical solutions are illustrated by single and dual capacitor converter examples that include pure resistive load and balance booster circuit. Theoretical results are supported by simulations and experimental verification.
Tracing PAH Emission in λ-Orionis Using COBE/DIRBE Data

We use archival COBE/DIRBE data to construct a map of polycyclic aromatic hydrocarbon (PAH) emission in the λ-Orionis region. The presence of the 3.3 μm PAH feature within the DIRBE 3.5 μm band and the corresponding lack of significant PAH spectral features in the adjacent DIRBE bands (1.25, 2.2, and 4.9 μm) enable estimation of the PAH contribution to the 3.5 μm data. Having the shortest wavelength of known PAH features, the 3.3 μm feature probes the smallest PAHs, which are also the leading candidates for carriers of anomalous microwave emission (AME). We use this map to investigate the association between the AME and the emission from PAH molecules. We find that the spatial correlation in λ-Orionis is higher between AME and far-infrared dust emission (as represented by the DIRBE 240 μm map) than it is between our PAH map and AME. This finding, in agreement with previous studies using PAH features at longer wavelengths, is in tension with the hypothesis that AME is due to spinning PAHs. However, the expected correlation between mid-infrared and microwave emission could potentially be degraded by different sensitivities of each emission mechanism to local environmental conditions even if PAHs are the carriers of both.
CohortVA: A Visual Analytic System for Interactive Exploration of Cohorts based on Historical Data

In history research, cohort analysis seeks to identify social structures and figure mobilities by studying the group-based behavior of historical figures. Prior works mainly employ automatic data mining approaches, lacking effective visual explanation. In this paper, we present CohortVA, an interactive visual analytic approach that enables historians to incorporate expertise and insight into the iterative exploration process. The kernel of CohortVA is a novel identification model that generates candidate cohorts and constructs cohort features by means of pre-built knowledge graphs constructed from large-scale history databases. We propose a set of coordinated views to illustrate identified cohorts and features coupled with historical events and figure profiles. Two case studies and interviews with historians demonstrate that CohortVA can greatly enhance the capabilities of cohort identifications, figure authentications, and hypothesis generation.
On the parameterized complexity of symmetric directed multicut

We study the problem Symmetric Directed Multicut from a parameterized complexity perspective. In this problem, the input is a digraph $D$, a set of cut requests $C=\{(s_1,t_1),\ldots,(s_\ell,t_\ell)\}$ and an integer $k$, and the task is to find a set $X \subseteq V(D)$ of size at most $k$ such that for every $1 \leq i \leq \ell$, $X$ intersects either all $(s_i,t_i)$-paths or all $(t_i,s_i)$-paths. Equivalently, every strongly connected component of $D-X$ contains at most one vertex out of $s_i$ and $t_i$ for every $i$. This problem is previously known from research in approximation algorithms, where it is known to have an $O(\log k \log \log k)$-approximation. We note that the problem, parameterized by $k$, directly generalizes multiple interesting FPT problems such as (Undirected) Vertex Multicut and Directed Subset Feedback Vertex Set. We are not able to settle the existence of an FPT algorithm parameterized purely by $k$, but we give three partial results: An FPT algorithm parameterized by $k+\ell$; an FPT-time 2-approximation parameterized by $k$; and an FPT algorithm parameterized by $k$ for the special case that the cut requests form a clique, Symmetric Directed Multiway Cut. The existence of an FPT algorithm parameterized purely by $k$ remains an intriguing open possibility.
Adaptive multigrid strategy for geometry optimization of large-scale three dimensional molecular mechanics

In this paper, we present an efficient adaptive multigrid strategy for the geometry optimization of large-scale three dimensional molecular mechanics. The resulting method can achieve significantly reduced complexity by exploiting the intrinsic low-rank property of the material configurations and by combining the state-of-the-art adaptive techniques with the hierarchical structure of multigrid algorithms. To be more precise, we develop a oneway multigrid method with adaptive atomistic/continuum (a/c) coupling, e.g., blended ghost force correction (BGFC) approximations with gradient-based a posteriori error estimators on the coarse levels. We utilize state-of-the-art 3D mesh generation techniques to effectively implement the method. For 3D crystalline defects, such as vacancies, micro-cracks and dislocations, compared with brute-force optimization, complexity with superior rates can be observed numerically, and the strategy has a five-fold acceleration in terms of CPU time for systems with $10^8$ atoms.
Planning for Automated Vehicles with Human Trust

Recent work has considered personalized route planning based on user profiles, but none of it accounts for human trust. We argue that human trust is an important factor to consider when planning routes for automated vehicles. This article presents a trust-based route-planning approach for automated vehicles. We formalize the human-vehicle interaction as a partially observable Markov decision process (POMDP) and model trust as a partially observable state variable of the POMDP, representing the human’s hidden mental state. We build data-driven models of human trust dynamics and takeover decisions, which are incorporated in the POMDP framework, using data collected from an online user study with 100 participants on the Amazon Mechanical Turk platform. We compute optimal routes for automated vehicles by solving optimal policies in the POMDP planning and evaluate the resulting routes via human subject experiments with 22 participants on a driving simulator. The experimental results show that participants taking the trust-based route generally reported more positive responses in the after-driving survey than those taking the baseline (trust-free) route. In addition, we analyze the trade-offs between multiple planning objectives (e.g., trust, distance, energy consumption) via multi-objective optimization of the POMDP. We also identify a set of open issues and implications for real-world deployment of the proposed approach in automated vehicles.
User Evaluation of Culture-to-Culture Image Translation with Generative Adversarial Nets

—The article introduces the concept of image “cultur-ization,” i.e., deﬁned as the process of altering the “brushstroke of cultural features” that make objects perceived as belonging to a given culture while preserving their functionalities. First, we deﬁned a pipeline for translating objects’ images from a source to a target cultural domain based on state-of-the-art Generative Adversarial Networks. Then, we gathered data through an online questionnaire to test four hypotheses concerning the impact of images belonging to different cultural domains on Italian participants. As expected, results depend on individual tastes and preferences: however, they are in line with our conjecture that some people, during the interaction with an intelligent system, might prefer to be shown images whose cultural domain has been modiﬁed to match their cultural background.
Cardiac troponin T in extracellular vesicles as a novel biomarker in human cardiovascular disease

Dear Editor, Soluble cardiac troponin T (cTnT), an indicator of myocardial injury and stress, is used in decision management for patients with cardiovascular disease (CVD). As highly sensitive assays can detect elevated concentrations of cTnT even in healthy individuals (e.g. outside ofmyocardial necrosis, electrocardiographic changes or angina) and cannot distinguish among disease conditions,1,2 a comprehensive understanding of the cTnT-secretome is an unmet need. Within the secretome, cTnT is not only present as a soluble factor but may also be contained within extracellular vesicles (EVs). 3 EVs are nanoscale particles secreted by all cells, the cargoes of which can reflect the molecular composition of the cells of origin4 and indicate disease or injury.5 As EVs are easily sampled from plasma,6 they are being developed as a ‘liquid’ biopsy reflecting the disease state from the tissue of origin. Here, we advanced a fluorescence-based super-resolution microscopy technique, quantitative single-molecule localization microscopy (qSMLM), to robustly characterize cTnT-positive EVs. Importantly, we provide the first report of cTnT-secretome across a spectrum of CVDs. EVs were purified from induced pluripotent stem cell– derived cardiomyocyte cell media (CCM), representing a source of cardiomyocyte-derived EVs (Figure S1), and patient plasma (Figures S2): healthy subjects (n = 5), patients with heart failure (HF; n = 5), hypertrophic cardiomyopathy (n = 3), type 1 myocardial infarction (MI-TI, n = 5) or type 2 myocardial infarction (MI-TII; n = 5) and chronic kidney disease (CKD; n = 5). In all cases (Figures S1 and S2), EVs had intact morphology and contained canonical EV markers (tetraspanins CD9, CD63, CD81; luminal marker TSG101) with low amounts of soluble proteins. According to dot blots (Figure S2C), the CD81 content of patient EVs was highly variable, whereas combined tetraspanins had more uniform expression. Table S1 shows patient characteristics. Control patients were
A Consistent Dual-MRC Framework for Emotion-cause Pair Extraction

Emotion-cause pair extraction (ECPE) is a recently proposed task that aims to extract the potential clause pairs of emotions and its corresponding causes in a document. In this article, we propose a new paradigm for the ECPE task. We cast the task as a two-turn machine reading comprehension (MRC) task, i.e., the extraction of emotions and causes is transformed to the task of identifying answer clauses from the input document specific to a query. This two-turn MRC formalization brings several key advantages: First, the QA manner provides an explicit pairing way to identify causes specific to the target emotion; second, it provides a natural way of jointly modeling the emotion extraction, the cause extraction, and the pairing of emotion and cause; and third, it allows us to exploit the well-developed MRC models. Based on the two-turn MRC formalization, we propose a dual-MRC framework to extract emotion-cause pairs in a dual-direction way, which enables a more comprehensive coverage of all pairing cases. Furthermore, we propose a consistent training strategy for the second-turn query, so the model is able to filter the errors produced by the first turn at inference. Experiments on two benchmark datasets demonstrate that our method outperforms previous methods and achieves state-of-the-art performance. All the code and data of this work can be obtained at https://github.com/zifengcheng/CD-MRC.
Architecture of the MKK6-p38α complex defines the basis of MAPK specificity and activation

The MAP kinase p38α is a central component of signalling in inflammation and the immune response and is, therefore, an important drug target. Little is known about the molecular mechanism of its activation by double-phosphorylation from MAP2Ks, due to the challenge of trapping a transient and dynamic hetero-kinase complex. Here, we applied a multidisciplinary approach to generate the first structure of p38α in complex with its MAP2K MKK6 and understand the activation mechanism. Integrating cryo-EM with MD simulations, HDX-MS and in cellulo experiments, we demonstrate a dynamic, multi-step, phosphorylation mechanism, reveal new catalytically relevant interactions, and show that MAP2K disordered N-termini determine pathway specificity. Our work captures, for the first time, a fundamental step of cell signalling: a kinase phosphorylating its downstream target kinase. One-Sentence Summary Integrative Cryo-EM and MD analysis of an active hetero-kinase complex reveals details of cellular signal transmission
Supraorbital whiskers act as wind-antennae in rat anemotaxis

We know little about mammalian anemotaxis, wind-sensing. Recently, however, Hartmann and colleagues showed whisker-based anemotaxis in rats. To investigate how whiskers sense airflow, we tracked whisker tips in anesthetized or cadaver rats under no airflow, low airflow and high (fan-blowing) airflow. Whisker tips showed little movement under no airflow conditions and all whisker tips moved during high airflow. Low airflow conditions – most similar to naturally occurring wind stimuli – engaged whisker tips differentially. Most whiskers moved little, the long supraorbital whisker showed maximal displacement and α, A1, β, and γ whiskers also showed movements. The long supraorbital whisker differs from other whiskers in its exposed dorsal position, upward bending, length and thin diameter. Ex vivo extracted long supraorbital whiskers also showed exceptional airflow displacement, suggesting whisker-intrinsic biomechanics mediate the unique airflow-sensitivity. Micro computed tomography revealed that the ring-wulst – the follicle structure receiving the most sensitive afferents – was more complete/ closed in supraorbital and other wind-sensitive whiskers than in non-wind-sensitive whiskers, suggesting specialization of the supraorbital for omni-directional sensing. We localized and targeted the cortical supraorbital whisker representation in simultaneous Neuropixels recordings with D/E-row whisker barrels. Responses to wind-stimuli were stronger in the supraorbital whisker representation than in D/E-row barrel cortex. We assessed the behavioral significance of whiskers in an airflow-sensing paradigm. We observed that rats spontaneously turn towards airflow stimuli in complete darkness. Selective trimming of wind-responsive whiskers diminished airflow turning responses more than trimming of non-wind-responsive whiskers. Lidocaine injections targeted to supraorbital whisker follicles also diminished airflow turning responses compared to control injections. We conclude that supraorbital whiskers act as wind antennae. New and Noteworthy Animals rely on sensory processing of airflow (anemotaxis) to guide navigation and survival. We examined mechanisms of rat anemotaxis by combining whisker tracking, biomechanical analysis, micro computed tomography of follicle structure, Neuropixels recordings in the barrel field, behavior of airflow turning and whisker interference by trimming and lidocaine injections. This diversity of methods led to a coherent pattern of results. Whiskers greatly differ in their airflow sensitivity and strongly wind-responsive whiskers – in particular long supraorbital whiskers – determine behavioral responses to airflow stimuli in rats.
Network predictions sharpen the representation of visual features for categorization

Models of visual cognition assume that brain networks predict the contents of a stimulus to facilitate its subsequent categorization. However, the specific network mechanisms of this facilitation remain unclear. Here, we studied them in 11 individual participants cued to the spatial location (left vs. right) and contents (Low vs. High Spatial Frequency, LSF vs. HSF) of an upcoming Gabor stimulus that they categorized. Using concurrent MEG recordings, we reconstructed in each participant the network that communicates the predicted contents and the network that represents these contents from the stimulus for categorization. We show that predictions of LSF vs. HSF propagate top-down from temporal to contra-lateral occipital cortex, with modulatory supervision from frontal cortex. In occipital cortex, predictions sharpen bottom-up stimulus LSF vs. HSF representations, leading to faster categorizations. Our results therefore reveal functional networks that predict visual contents to sharpen their representations from the stimulus to facilitate categorization behavior.
Directed differentiation of human iPSCs to functional ovarian granulosa-like cells via transcription factor overexpression

An in vitro model of human ovarian follicles would greatly benefit the study of female reproduction. Ovarian development requires the combination of germ cells and their supporting somatic cells, known as granulosa cells. Whereas efficient protocols exist for generating human primordial germ cell-like cells (hPGCLCs) from human iPSCs, a method of generating granulosa cells has been elusive. Here we report that simultaneous overexpression of two transcription factors (TFs) can direct the differentiation of human iPSCs to granulosa-like cells. We elucidate the regulatory effects of several granulosa-related TFs, and establish that overexpression of NR5A1 and either RUNX1 or RUNX2 is necessary and sufficient to generate granulosa-like cells. Our granulosa-like cells form ovary-like organoids (ovaroids) when aggregated with hPGCLCs, and recapitulate key ovarian phenotypes including support of germ cell maturation, follicle formation, and steroidogenesis. This model system will provide unique opportunities for studying human ovarian biology, and may enable the development of therapies for female reproductive health.
The olfactory bulb carries out concentration invariance calculations by itself and does it very quickly

The olfactory bulb is known to carry out computations for the olfactory perception of concentration invariance of odor recognition, a perception that is essential for life as we know it. However it is not known whether these computations require the extensive feedback to the bulb from the many brain regions which send this feedback. We have measured the concentration dependence of the mitral cell output of the bulb before and after blocking this feedback by lidocaine infusion into the medial olfactory peduncle. Surprisingly we found that the concentration dependence of the mitral cell output was unaffected by the lidocaine block of feedback. Furthermore the computation is rapid; it is complete within a single 250 msec inhalation. The computations for concentration invariance are most likely carried out within the olfactory bulb itself and they are carried out quickly.
Tissue-specific regulation of gene expression via unproductive splicing

Eukaryotic gene expression is regulated post-transcriptionally by a mechanism called unproductive splicing, in which mRNA is triggered to degradation by the nonsense-mediated decay (NMD) pathway as a result of regulated alternative splicing (AS). Only a few dozen unproductive splicing events (USEs) are currently documented, and many more remain to be identified. Here, we analyzed RNA-seq experiments from the Genotype-Tissue Expression (GTEx) Consortium to identify USEs, in which an increase in the NMD isoform splicing rate is accompanied by tissue-specific downregulation of the host gene. Further, to characterize RBPs that regulate USEs, we superimposed these results with RNA-binding protein (RBP) footprinting data and experiments on the response of the transcriptome to the perturbation of expression of a large panel of RBPs. Concordant tissue-specific changes between the expression of RBP and USE splicing rate revealed a high-confidence regulatory network including 27 tissue-specific USEs with strong evidence of RBP binding. Among them, we found previously unknown PTBP1-controlled events in the DCLK2 and IQGAP1 genes, for which we confirmed the regulatory effect using siRNA-knockdown experiments in the A549 cell line. In sum, we present a transcriptomic pipeline that allows the identification of tissue-specific USEs, potentially many more than we have reported here using stringent filters.
Gamma (γ)-radiation stress response of the cyanobacterium Anabaena sp. PCC7120: Regulatory role of LexA and photophysiological changes

High radioresistance of the cyanobacterium, Anabaena sp. PCC7120 has been attributed to efficient DNA repair, protein recycling, and oxidative stress management. However, the regulatory network involved in these batteries of responses remains unexplored. In the present study, the role of a global regulator, LexA in modulating gamma (γ)-radiation stress response of Anabaena was investigated. Comparison of the cytosolic proteome profiles upon γ-radiation in recombinant Anabaena strains, AnpAM (vector-control) and AnlexA+ (LexA-overexpressing), revealed 41 differentially accumulated proteins, corresponding to 29 distinct proteins. LexA was found to be involved in the regulation of 27 of the corresponding genes based on the presence of AnLexA-Box, EMSA, and/or qRT-PCR studies. The majority of the regulated genes were found to be involved in C-assimilation either through photosynthesis or C-catabolism and oxidative stress alleviation. Photosynthesis, measured in terms of PSII photophysiological parameters and thylakoid membrane proteome was found to be affected by γ-radiation in both AnpAM and AnlexA+ cells, with LexA affecting them even under control growth conditions. Thus, LexA functioned as one of the transcriptional regulators involved in modulating γ-radiation stress response in Anabaena. This study could pave the way for a deeper understanding of the regulation of γ-radiation-responsive genes in cyanobacteria at large. Highlights γ-radiation alters PSII photophysiology and thylakoid proteome profile in Anabaena. LexA modulates the cytosolic and thylakoid proteome of Anabaena under γ-radiation. LexA functions as one of the regulators of radiation-responsive genes in Anabaena.