Miracle-dz/UniFAR-FTUs huggingface dataset:
Mimicking Better by Matching the Approximate Action Distribution

In this paper, we introduce MAAD, a novel, sample-efficient on-policy algorithm for Imitation Learning from Observations. MAAD utilizes a surrogate reward signal, which can be derived from various sources such as adversarial games, trajectory matching objectives, or optimal transport criteria. To compensate for the non-availability of expert actions, we rely on an inverse dynamics model that infers plausible actions distribution given the expert's state-state transitions; we regularize the imitator's policy by aligning it to the inferred action distribution. MAAD leads to significantly improved sample efficiency and stability. We demonstrate its effectiveness in a number of MuJoCo environments, both int the OpenAI Gym and the DeepMind Control Suite. We show that it requires considerable fewer interactions to achieve expert performance, outperforming current state-of-the-art on-policy methods. Remarkably, MAAD often stands out as the sole method capable of attaining expert performance levels, underscoring its simplicity and efficacy.
Sample-Efficient Learning of Novel Visual Concepts

Despite the advances made in visual object recognition, state-of-the-art deep learning models struggle to effectively recognize novel objects in a few-shot setting where only a limited number of examples are provided. Unlike humans who excel at such tasks, these models often fail to leverage known relationships between entities in order to draw conclusions about such objects. In this work, we show that incorporating a symbolic knowledge graph into a state-of-the-art recognition model enables a new approach for effective few-shot classification. In our proposed neuro-symbolic architecture and training methodology, the knowledge graph is augmented with additional relationships extracted from a small set of examples, improving its ability to recognize novel objects by considering the presence of interconnected entities. Unlike existing few-shot classifiers, we show that this enables our model to incorporate not only objects but also abstract concepts and affordances. The existence of the knowledge graph also makes this approach amenable to interpretability through analysis of the relationships contained within it. We empirically show that our approach outperforms current state-of-the-art few-shot multi-label classification methods on the COCO dataset and evaluate the addition of abstract concepts and affordances on the Visual Genome dataset.
The genetics‐morphology‐behavior trifecta: Unraveling the single greatest limitation affecting our understanding of chondrichthyan evolution

Abstract Sharks, rays, and chimaera form the clade Chondrichthyes, an ancient group of morphologically and ecologically diverse vertebrates that has played an important role in our understanding of gnathostome evolution. Increasingly, studies seek to investigate evolutionary processes operating within the chondrichthyan crown group, with the broad aim of understanding the driving forces behind the vast phenotypic diversity observed among its constituent taxa. Genetic, morphological, and behavioral studies have all contributed to our understanding of phenotypic evolution yet are typically considered in isolation in the context of Chondrichthyes. In this viewpoint, I discuss why such isolation is prevalent in the literature, how it constrains our understanding of evolution, and how it might be overcome. I argue that integrating these core fields of organismal biology is vital if we are to understand the evolutionary processes operating in contemporary chondrichthyan taxa and how such processes have contributed to past phenotypic evolution. Despite this, the necessary tools to overcome this major limitation already exist and have been applied to other taxa.
Physiological response and transcriptome analyses of leguminous Indigofera bungeana Walp. to drought stress

Objective Indigofera bungeana is a shrub with high quality protein that has been widely utilized for forage grass in the semi-arid regions of China. This study aimed to enrich the currently available knowledge and clarify the detailed drought stress regulatory mechanisms in I. bungeana, and provide a theoretical foundation for the cultivation and resistance breeding of forage crops. Methods This study evaluates the response mechanism to drought stress by exploiting multiple parameters and transcriptomic analyses of a 1-year-old seedlings of I. bungeana in a pot experiment. Results Drought stress significantly caused physiological changes in I. bungeana. The antioxidant enzyme activities and osmoregulation substance content of I. bungeana showed an increase under drought. Moreover, 3,978 and 6,923 differentially expressed genes were approved by transcriptome in leaves and roots. The transcription factors, hormone signal transduction, carbohydrate metabolism of regulatory network were observed to have increased. In both tissues, genes related to plant hormone signaling transduction pathway might play a more pivotal role in drought tolerance. Transcription factors families like basic helix-loop-helix (bHLH), vian myeloblastosis viral oncogene homolog (MYB), basic leucine zipper (bZIP) and the metabolic pathway related-genes like serine/threonine-phosphatase 2C (PP2C), SNF1-related protein kinase 2 (SnRK2), indole-3-acetic acid (IAA), auxin (AUX28), small auxin up-regulated rna (SAUR), sucrose synthase (SUS), sucrosecarriers (SUC) were highlighted for future research about drought stress resistance in Indigofera bungeana. Conclusion Our study posited I. bungeana mainly participate in various physiological and metabolic activities to response severe drought stress, by regulating the expression of the related genes in hormone signal transduction. These findings, which may be valuable for drought resistance breeding, and to clarify the drought stress regulatory mechanisms of I. bungeana and other plants.
Improving taxonomic classification of marine zooplankton by molecular approach: registration of taxonomically verified 18S and 28S rRNA gene sequences

Background Zooplankton plays an important role in the marine ecosystem. A high level of taxonomic expertise is necessary for accurate species identification based on morphological characteristics. As an alternative method to morphological classification, we focused on a molecular approach using 18S and 28S ribosomal RNA (rRNA) gene sequences. This study investigates how the accuracy of species identification by metabarcoding improves when taxonomically verified sequences of dominant zooplankton species are added to the public database. The improvement was tested by using natural zooplankton samples. Methods rRNA gene sequences were obtained from dominant zooplankton species from six sea areas around Japan and registered in the public database for improving the accuracy of taxonomic classifications. Two reference databases with and without newly registered sequences were created. Comparison of detected OTUs associated with single species between the two references was done using field-collected zooplankton samples from the Sea of Okhotsk for metabarcoding analysis to verify whether or not the newly registered sequences improved the accuracy of taxonomic classifications. Results A total of 166 sequences in 96 species based on the 18S marker and 165 sequences in 95 species based on the 28S marker belonging to Arthropoda (mostly Copepoda) and Chaetognatha were registered in the public database. The newly registered sequences were mainly composed of small non-calanoid copepods, such as species belonging to Oithona and Oncaea. Based on the metabarcoding analysis of field samples, a total of 18 out of 92 OTUs were identified at the species level based on newly registered sequences in the data obtained by the 18S marker. Based on the 28S marker, 42 out of 89 OTUs were classified at the species level based on taxonomically verified sequences. Thanks to the newly registered sequences, the number of OTUs associated with a single species based on the 18S marker increased by 16% in total and by 10% per sample. Based on the 28S marker, the number of OTUs associated with a single species increased by 39% in total and by 15% per sample. The improved accuracy of species identification was confirmed by comparing different sequences obtained from the same species. The newly registered sequences had higher similarity values (mean >0.003) than the pre-existing sequences based on both rRNA genes. These OTUs were identified at the species level based on sequences not only present in the Sea of Okhotsk but also in other areas. Discussion The results of the registration of new taxonomically verified sequences and the subsequent comparison of databases based on metabarcoding data of natural zooplankton samples clearly showed an increase in accuracy in species identification. Continuous registration of sequence data covering various environmental conditions is necessary for further improvement of metabarcoding analysis of zooplankton for monitoring marine ecosystems.
Precise mapping of one classic and three novel GluRIIA mutants in Drosophila melanogaster

Mutation of the Drosophila melanogaster GluRIIA gene or pharmacological agents targeting it are commonly used to assess homeostatic synaptic function at the larval neuromuscular junction (NMJ). The commonly used mutation, GluRIIA SP16 , is a null allele created by a large and imprecise excision of a P-element which affects GluRIIA and multiple upstream genes. Here we mapped the exact bounds of the GluRIIA SP16 allele, refined a multiplex PCR strategy for positive identification of GluRIIA SP16 in homozygous or heterozygous backgrounds, and sequenced and characterized three new CRISPR-generated GluRIIA mutants. We found the three new GluRIIA alleles are apparent nulls that lack GluRIIA immunofluorescence signal at the 3 rd instar larval NMJ and are predicted to cause premature truncations at the genetic level. Further, these new mutants have similar electrophysiological outcomes as GluRIIA SP16 , including reduced miniature excitatory postsynaptic potential (mEPSP) amplitude and frequency compared to controls, and they express robust homeostatic compensation as evidenced by normal excitatory postsynaptic potential (EPSP) amplitude and elevated quantal content. These findings and new tools extend the capacity of the D. melanogaster NMJ for assessment of synaptic function.
Transonic aeroelastic numerical simulation in aeronautical engineering

A lower–upper symmetric Gauss–Seidel (LU-SGS) subiteration scheme is constructed for time-marching of the fluid equations. The Harten–Lax–van Leer–Einfeldt–Wada (HLLEW) scheme is used for the spatial discretization. The same subiteration formulation is applied directly to the structural equations of motion in generalized coordinates. Through subiteration between the fluid and structural equations, a fully implicit aeroelastic solver is obtained for the numerical simulation of fluid/structure interaction. To improve the ability for application to complex configurations, a multiblock grid is used for the flow field calculation and transfinite interpolation (TFI) is employed for the adaptive moving grid deformation. The infinite plate spline (IPS) and the principal of virtual work are utilized for the data transformation between the fluid and structure. The developed code was first validated through the comparison of experimental and computational results for the AGARD 445.6 standard aeroelastic wing. Then, the flutter character of a tail wing with control surface was analyzed. Finally, flutter boundaries of a complex aircraft configuration were predicted.
Clinical insights into small cell lung cancer: Tumor heterogeneity, diagnosis, therapy, and future directions

Small cell lung cancer (SCLC) is characterized by rapid growth and high metastatic capacity. It has strong epidemiologic and biologic links to tobacco carcinogens. Although the majority of SCLCs exhibit neuroendocrine features, an important subset of tumors lacks these properties. Genomic profiling of SCLC reveals genetic instability, almost universal inactivation of the tumor suppressor genes TP53 and RB1, and a high mutation burden. Because of early metastasis, only a small fraction of patients are amenable to curative‐intent lung resection, and these individuals require adjuvant platinum‐etoposide chemotherapy. Therefore, the vast majority of patients are currently being treated with chemoradiation with or without immunotherapy. In patients with disease confined to the chest, standard therapy includes thoracic radiotherapy and concurrent platinum‐etoposide chemotherapy. Patients with metastatic (extensive‐stage) disease are treated with a combination of platinum‐etoposide chemotherapy plus immunotherapy with an anti‐programmed death‐ligand 1 monoclonal antibody. Although SCLC is initially very responsive to platinum‐based chemotherapy, these responses are transient because of the development of drug resistance. In recent years, the authors have witnessed an accelerating pace of biologic insights into the disease, leading to the redefinition of the SCLC classification scheme. This emerging knowledge of SCLC molecular subtypes has the potential to define unique therapeutic vulnerabilities. Synthesizing these new discoveries with the current knowledge of SCLC biology and clinical management may lead to unprecedented advances in SCLC patient care. Here, the authors present an overview of multimodal clinical approaches in SCLC, with a special focus on illuminating how recent advancements in SCLC research could accelerate clinical development.
Neutrinos from gamma-ray bursts, and the multi-messenger connection

In this work, we take a look at the connection of gamma-ray bursts (GRBs) and ultra-high-energy cosmic rays (UHECR) as well as the possibilities how to verify this connection. The currently most promising approach is based on the detection of high-energy neutrinos, which are associated with the acceleration of cosmic rays. We detail how the prompt gamma-ray emission is connected to the prediction of a neutrino signal. We focus on the interactions of photons and protons in this regard. At the example of the current ANTARES GRB neutrino analysis, we show the differences between numerical predictions and older analytical methods. Moreover, we discuss the possibilities how cosmic ray particles can escape from GRBs, assuming that UHECR are entirely made up of protons. For this, we compare the commonly assumed neutron escape model with a new component of direct proton escape. Additionally, we will show that the different components, which contribute to the cosmic ray flux, strongly depend on the burst parameters, and test the applicability on some chosen GRBs. In a further step, we continue with the considerations regarding the connection of GRBs and UHECR by connecting the GRB source model with the cosmic ray observations using a simple cosmic ray propagation code. We test if it is possible to achieve the observed cosmic ray energy densities with our simple model and what the consequences are regarding the prompt GRB neutrino flux predictions as well as the cosmogenic neutrinos. Furthermore, we consider the question of neutrino lifetime and how it affects the prompt GRB neutrino flux predictions. In a final chapter, we show that it is possible to apply the basic source model with photohadronic interactions to other types of sources, using the example of the microquasar Cygnus X-3.
Network-Based H_∞ Output Tracking Control for a Type of Discrete Time Systems

This paper investigated the problem of H∞output tracking for a type of discrete network-based control systems subjected to quantization and data dropout. The state of controlled system and the reference model state were quantized before being communicated. The quantization error was treated as sector-bounded uncertainty. The effect of the random packet loss was modelled as a Bernoulli process. Later, a sufficient condition was proposed for the existence of H∞tracking controllers in terms of linear matrix inequalities(LMIs). The proposed controller could guarantee the output of the closed-loop networked control system tracks that of a given reference model well in the H∞sense.Finally, a numerical example was prensented to show the effectiveness and usfulness of the proposed H∞output tracking design.
A Sensitivity Analysis of Varying Parameter Econometric Models

This paper is concerned with the Kalman filter model, a linear regression model in which the coefficient vector is assumed to be a random vector which follows a first-order Markov process. Four parameter sets, which we denote T, r,2, Vu, and P(0), must be specified before minimum mean squared linear estimators of the coefficient vector P(t), and hence the dependent variable y(t), can be obtained. These parameter sets typically will not be known in an economic context, and estimation or ad hoc specification will be necessary; in either case, misspecification of the parameter sets is likely. The purpose of this paper is to examine via simulation the effects of such misspecifications on the estimation of the fl(t) and the y(t).
Fusion of multispectral and panchromatic images based on PCA and NSCT

A novel fusion method is proposed for multispectral and panchromatic satellite images using Principal Component Analysis(PCA)and Nonsubsampled Contourlet Transform(NSCT). This method first performs PCA on MS, and NSCT on PAN and the first principal componen(tPC1)to get corresponding low-frequency and high-fre-quency coefficients. Then fuses the approximation coefficients using PCA again for the tradeoff between the spectral and spatial information, and fuses the subbands coefficients based on Structural Similarity Index(SSIM)and lo- cal Sobel average gradient for the spatial detail information. A fused image is formed through inverse NSCT and inverse PCA. Experimental results show that the proposed fusion method can effectively preserve spectral information while improving the spatial quality, and outperforms the general IHS-, PCA-, Wavelet-, Contourlet-based fusion methods.
Ionosphere Effect Mitigation for Single- Frequency Precise Point Positioning

Precise Point Positioning (PPP) is a stand-alone positioning technique that has continuously increased the interest of the GNSS community in the last years, as the accuracy of the precise satellite orbit and clock data products has achieved centimeter-level. Combining these products with dual-frequency GNSS receiver data, the PPP approach is able to provide solutions at centimeter to decimeter level. Apart from the dual-frequency receiver users, there is a broad range of applications that use single-frequency-only receivers. For these users, the ionosphere represents the most critical source of error. This paper carries out an initial investigation on PPP performance using single-frequency code and carrierphase data with different approaches to mitigate the ionospheric effect, such as the broadcast ionospheric model, Global Ionospheric Maps and Wide-Area Real Time Kinematic derived ionospheric corrections. An alternative way to remove the ionosphere influence is to take advantage of the fact that the group delay in the range observable and the carrier phase advance have the same magnitude but are opposite in sign. This paper also investigates the potential of this approach. Data retrieved from IGS stations covering different latitudes and solar activity periods (high, medium, low) are considered. The results show that sub-meter-level positioning accuracy can be obtained with single-frequency-only data utilizing proper ionospheric effect mitigation methods, under optimal multipath conditions. These initial results open the way to a broader study covering other singlefrequency PPP ionospheric effect mitigation strategies, as well as harsher multipath conditions. 2508 22nd International Meeting of the Satellite Division of The Institute of Navigation, Savannah, GA, September 22-25, 2009
INVESTIGATION OF THE PATHOLOGICAL EFFECTS OF HISTONES, DNA, AND NUCLEOSOMES IN A MURINE MODEL OF SEPSIS

ABSTRACT Background: In sepsis, neutrophil extracellular traps (NETs) are an important interface between innate immunity and coagulation. The major structural component of neutrophil extracellular traps is nucleosomes (DNA-histone complexes). In vitro, DNA and histones exert procoagulant/cytotoxic effects whereas nucleosomes are not harmful. However, whether DNA, histones, and/or nucleosomes exert harmful effects in vivo remain unclear. Objectives: (1) The aims of the study are to investigate the cytotoxic effects of nucleosomes ± DNase I and heparin in vitro and (2) to investigate whether DNA, histones, and/or nucleosomes are harmful when injected into healthy and septic mice. Methods: The cytotoxic effects of DNA, histones, and nucleosomes (± DNaseI or ±heparin) were assessed in HEK293 cells. Mice underwent cecal ligation and puncture or sham surgery and then received injections of DNA (8 mg/kg), histones (8.5 mg/kg), or nucleosomes at 4 and 6 h. Organs and blood were harvested at 8 h. Cell-free DNA, IL-6, thrombin-anti-thrombin, and protein C were quantified from plasma. Results: In vitro, incubation of HEK293 cells with DNaseI-treated nucleosomes reduced cell survival compared with nucleosome-treated cells, suggesting that DNaseI releases cytotoxic histones from nucleosomes. Addition of heparin to DNaseI-treated nucleosomes rescued cell death. In vivo, administration of histones to septic mice increased markers of inflammation (IL-6) and coagulation (thrombin-anti-thrombin), which was not observed in sham or septic mice administered DNA or nucleosomes. Conclusions: Our studies suggest that DNA masks the harmful effects of histones in vitro and in vivo. Although administration of histones contributed to the pathogenesis of sepsis, administration of nucleosomes or DNA was not harmful in healthy or septic mice.
Diagnostic Rate of Malignant Lymphoma Using Soluble Interleukin 2 Receptor Levels in Patients with Cervical Lymphadenopathy

Abstract Background and Objectives Cervical lymph node enlargement is observed in various diseases, including malignant lymphoma (ML). Open biopsy of the enlarged lymph node is frequently required for diagnosis, especially when ML is suspected. Serum levels of soluble interleukin 2 receptor (sIL-2R) may be useful as a biomarker of ML. This study aimed to determine whether the measurement of serum sIL-2R levels might be useful to diagnose ML. Materials and Methods We retrospectively reviewed the data of 281 patients who had undergone open cervical lymph node biopsy at our institution between 2015 and 2019, including 157 males and 124 females (age range, 5–90 years). Data on the patients' age, final diagnosis, and serum sIL-2R levels were obtained from their medical records. Results Overall, 184 cases of MLs and 97 cases of other diseases (non-MLs [NMLs]) were recorded. The mean age was significantly higher and mean serum sIL-2R levels were significantly higher in the ML group than in the NML group. In the ML group, the serum sIL-2R levels were significantly higher in patients with T cell lymphoma than in those with B cell lymphoma. The area under the receiver operating characteristic curve of the serum sIL-2R level for predicting ML was 0.711, and a serum sIL-2R level of 1,246 U/mL was associated with the maximum value of the sensitivity + specificity for the diagnosis of ML. Multivariate analysis revealed that the area under the receiver operating characteristic curve increased to 0.758 for patients aged >61 years and patients with serum sIL-2R levels of >1,246 U/mL. Conclusions Among patients presenting with cervical lymphadenopathy, the measurement of serum sIL-2R levels could be useful for distinguishing between patients with and without ML, with a cutoff level of 1,246 U/mL for the diagnosis of ML.