Miracle-dz/UniFAR-FTUs huggingface dataset:
Coupling minimization with obstacles avoidance of free-floating space robots based on hybrid map in configuration space

To avoid the saturation of momentum wheels and the harm due to the thruster plume during the on-orbital manipulation, space robots usually stay in a free-floating state which follows the linear and angular momentum conservation leading to a kinematic coupling effect of the satellite base and the space manipulator. Emphasizing the stability of satellite base and execution safety, it is significant to minimize the kinematic coupling effect as well as avoid obstacles in the environment. Nevertheless, coupling minimization and obstacles avoidance are considered separately in previous work. By applying a hybrid map in the Configuration space, this article proposes a unified method dealing with the above two problems together. First, coupling factors are defined to evaluate the kinematic coupled effect which can be described by a coupling map; second, an obstruction map is generated by transforming obstacles in the Cartesian space to the Configuration space; the proposed hybrid map is finally generated from an overlay of a coupling map and an obstruction map. Numerical simulations verify the effectiveness of the method on a two degree-of-freedom planar space robot.
Zearalenone-induced Deterioration in Reproductive Performance and Seminal Plasma Biochemistry of Male Rabbits

Zearalenone (ZEA) is a nonsteroidal mycotoxin, produced by various fungi of the Fusarium genus; Zearalenone exhibits estrogenic and anabolic properties in several animal species, including human beings. Zearalenone contamination of food is caused either by direct contamination of grains, fruits, and their product or by ―carry-over‖ of mycotoxins and their metabolites in animal tissues, milk, and eggs after intake of contaminated feedstuff.Despite Zearalenone has toxicity and carcinogenicity.Detoxification strategies for contaminated foods and feeds to reduce or eliminate the toxic effects of ZEA by chemical, physical, and biological methods are crucial to improve food safety, prevent economic losses, and reclaim contaminated productsHowever; there is no enough data on the reproductive toxicity of Zearalenone in adult male.Therefore, the present investigation aimed to elucidate the toxicity of different doses of Zearalenone on reproductive performance, enzyme activities in seminal plasma and growth performance of males New Zealand white rabbits. Twenty rabbits were divided into 4 equal groups, first group was used as control, second group was treated with 0.5 μg/kg BW, third group was treated with 5 μg/kg BW and the fourth group was treated with 10 μg/kg BW of Zearalenone. Animals were treated orally every day for 12 weeks. Results obtained showed that Zearalenone significantly (P < 0.05) decreased libido (by increasing the reaction time), ejaculate volume, sperm concentration, total sperm output, sperm motility (%), total motile sperms per ejaculate (TMS), packed sperm volume (PSV), total functional sperm fraction (TFSF), normal and live sperms and semen initial fructose. While, initial hydrogen ion concentration (pH) and dead and abnormal sperms were increased (P < 0.05). Live body weight (LBW), feed intake (FI) and, aspartate aminotransferase (AST), alanine aminotransferase (ALT) and acid phosphatase (ACP) were significantly (P < 0.05) decreased. It was suggested that Zearalenone exerted a significant adverse effect on reproductive performance of male rabbits and the effects were in a dosedependent manner.
New mutant mouse models clarify the role of NAIPs, phosphorylation, NLRP3, and tumors in NLRC4 inflammasome activation

The NAIP/NLRC4 inflammasome is a cytosolic sensor of bacteria that activates Caspase-1 and initiates potent downstream immune responses. Structural, biochemical, and genetic data all demonstrate that the NAIP proteins act as receptors for specific bacterial ligands, while NLRC4 is a downstream adaptor protein that multimerizes with NAIPs to form a macromolecular structure called an inflammasome. However, several aspects of NLRC4 biology remain unresolved. For example, in addition to its clear function in responding to bacteria, NLRC4 has also been proposed to initiate anti-tumor responses, though the underlying mechanism is unknown. NLRC4 has also been shown to be phosphorylated on serine 533, and this modification was suggested to be important for NLRC4 function. In the absence of S533 phosphorylation, it was further proposed that another inflammasome component, NLRP3, can induce NLRC4 activation. We generated a new Nlrc4-deficient mouse line as well as mice encoding phosphomimetic S533D and non-phosphorylatable S533A NLRC4 proteins. Using these genetic models in vivo and in vitro, we fail to observe a role for phosphorylation in NLRC4 inflammasome function. Furthermore, we find no role for NLRP3 in NLRC4 function, or for NLRC4 in a model of melanoma. These results simplify and clarify our understanding of the mechanism of NAIP/NLRC4 activation and its biological functions.
The complete chloroplast genome sequence of a vulnerable legume species Dalbergia tonkinensis prain in Vietnam

Abstract Dalbergia tonkinensis is a critically vulnerable tree species that is distributed in Vietnam and Hainan Island of China. The complete chloroplast genome sequence of D. tonkinensis was characterized using Illumina pair-end sequencing. The cpDNA is 156,086 bp in length and contains a pair of 25,720 bp inverted repeats, one large single copy region of 85,761 bp, and one small single copy region of 18,885 bp. It contains 131 genes including 86 protein-coding genes, 36 tRNAs, eight rRNAs, and one pseudogene. The overall G + C content of the whole genome is 36.1%. Phylogenetic analysis based on 35 chloroplast genomes of Papilionoideae including Cercis glabra (as an outgroup) indicates that all the species of the Dalbergioids sensu lato formed a monophyletic clade and D. tonkinensis formed a sister relationship with the D. hainanensis and D. odorifera group.
Phasic dopamine enhances the distinct decoding and perceived salience of stimuli

Subjects learn to assign value to stimuli that predict outcomes. Novelty, rewards or punishment evoke reinforcing phasic dopamine release from midbrain neurons to ventral striatum that mediates expected value and salience of stimuli in humans and animals. It is however not clear whether phasic dopamine release is sufficient to form distinct engrams that encode salient stimuli within these circuits. We addressed this question in awake mice. Evoked phasic dopamine induced plasticity selectively to the population encoding of coincidently presented stimuli and increased their distinctness from other stimuli. Phasic dopamine thereby enhanced the decoding of previously paired stimuli and increased their perceived salience. This dopamine-induced plasticity mimicked population coding dynamics of conditioned stimuli during reinforcement learning. These findings provide a network coding mechanism of how dopaminergic learning signals promote value assignment to stimulus representations.
Resveratrol blocks atherosclerosis development by inhibiting IL-1β in macrophages induced by cholesterol

Resveratrol is a polyphenolic compound that exhibits antiinflammatory and cardioprotective properties. In this study we investigated the protective role of resveratrol on the inflammatory activation of macrophages during pathogenesis of atherosclerosis. Macrophage Ana-1 cells were stimulated by cholesterol and resveratrol, and the cell culture supernatant was collected to treat human umbilical vein endothelial cells (HUVECs). The release of IL-1? into the Ana-1 cell supernatant was quantified by ELISA. Expression of the adhesion molecule ICAM-1 and E-selectin in HUVECs were examined by Western-blotting. Additionally, the adhesion of monocytes in HUVECs under different conditions was tested by cell adhesion analyses. The results indicated that the high cholesterol treatment increased the expression level of IL-1? , while pretreatment with resveratrol inhibited this induction of IL-1? in Ana-1 cells. Resveratrol inhibited the adhesion of monocytes to the endothelium at least partly through inhibition of IL-1? expression in macrophages. Moreover, the expression level of caveolin-1 significantly increased after the pretreatment with resveratrol, indicating that resveratrol enhances reverse cholesterol transport (RCT) in macrophages. Our study indicated that resveratrol has significant antiinflammatory effects and can be considered as a candidate molecule to prevent atherosclerosis.
Prism adaptation modulates connectivity of the intraparietal sulcus with multiple brain networks

Prism adaptation (PA) alters spatial cognition according to the direction of visual displacement by temporarily modifying sensorimotor mapping. Right-shifting prisms (right PA) improve neglect of left space in patients, possibly by decreasing activity in the left hemisphere and increasing it in the right. Left PA shifts attention to the right in healthy individuals by an opposite mechanism. However, functional imaging studies of PA are inconsistent, perhaps because of differing activation tasks. We measured resting-state functional connectivity (RSFC) in healthy individuals before and after PA. Right, vs. left, PA decreased RSFC in the navigation network defined by the right posterior parietal cortices (PPCs), hippocampus, and cerebellum. Right PA, relative to baseline, increased RSFC between regions within both PPCs and between the PPCs and the right middle frontal gyrus, whereas left PA decreased RSFC between these regions. These results show that right PA modulates connectivity within the right-hemisphere navigation network and shifts attention leftward by increasing connectivity in the right frontoparietal network and left PA produces essentially opposite effects, consistent with the interhemispheric competition model. These finding explain the action of PA on intact cognition and will help optimize interventions in neglect patients.
Pharmacokinetic and Pharmacodynamic Properties of Drug Delivery Systems

The use of drug delivery systems (DDS) is an attractive approach to facilitate uptake of therapeutic agents at the desired site of action, particularly when free drug has poor pharmacokinetics/biodistribution (PK/BD) or significant off-site toxicities. Successful translation of DDS into the clinic is dependent on a thorough understanding of the in vivo behavior of the carrier, which has, for the most part, been an elusive goal. This is, at least in part, due to significant differences in the mechanisms controlling pharmacokinetics for classic drugs and DDSs. In this review, we summarize the key physiologic mechanisms controlling the in vivo behavior of DDS, compare and contrast this with classic drugs, and describe engineering strategies designed to improve DDS PK/BD. In addition, we describe quantitative approaches that could be useful for describing PK/BD of DDS, as well as critical steps between tissue uptake and pharmacologic effect.
Nitrogen assimilation in picocyanobacteria inhabiting the oxygen‐deficient waters of the eastern tropical North and South Pacific

Prochlorococcus and Synechococcus are the most abundant free‐living photosynthetic microorganisms in the ocean. Uncultivated lineages of these picocyanobacteria also thrive in the dimly illuminated upper part of oxygen‐deficient zones (ODZs), where an important portion of ocean nitrogen (N) loss takes place via denitrification and anaerobic ammonium oxidation. Recent metagenomic studies revealed that ODZ Prochlorococcus have the genetic potential for using different N forms, including nitrate and nitrite, uncommon N sources for Prochlorococcus, but common for Synechococcus. To determine which N sources ODZ picocyanobacteria are actually using in nature, the cellular 15N natural abundance (δ15N) and assimilation rates of different N compounds were determined using cell sorting by flow cytometry and mass spectrometry. The natural δ15N of the ODZ Prochlorococcus varied from −4.0‰ to 13.0‰ (n = 9), with 50% of the values in the range of −2.1–2.6‰. While the highest values suggest nitrate use, most observations indicate the use of nitrite, ammonium, or a mixture of N sources. Meanwhile, incubation experiments revealed potential assimilation rates of ammonium and urea in the same order of magnitude as that expected for total N in several environments including ODZs, whereas rates of nitrite and nitrate assimilation were very low. Our results thus indicate that reduced forms of N and nitrite are the dominant sources for ODZ picocyanobacteria, although nitrate might be important on some occasions. ODZ picocyanobacteria might thus represent potential competitors with anammox bacteria for ammonium and nitrite, with ammonia‐oxidizing archaea for ammonium, and with nitrite‐oxidizing bacteria for nitrite.
Golgi-localized PAQR4 mediates Anti-apoptotic Ceramidase Activity in Breast Cancer

The metabolic network of sphingolipids plays important roles in cancer biology. Prominent sphingolipids include ceramides and sphingosine-1-phosphate that regulate multiple aspects of growth, apoptosis and cellular signaling. Although many significant enzymatic regulators of the sphingolipid pathway have been described in detail, the list is currently incomplete. Here, we applied a systemic approach to identify and molecularly define progestin and adipoQ receptor family member IV (PAQR4) as a Golgi-localized ceramidase. We find PAQR4 to be ∼5 fold upregulated in breast cancer compared to matched control tissue and that its overexpression correlate with disease-specific survival rates in breast cancer. PAQR4 is a seven transmembrane protein, and depletion of PAQR4 leads to cellular apoptosis through accumulation of ceramides. Our findings establish PAQR4 as Golgi-localized ceramidase required for cellular growth in breast cancer.
The effects of data adequacy and calibration size on the accuracy of presence-only species distribution models

Presence-only data used to develop species distribution models are often biased towards areas that are frequently surveyed. Furthermore, the size of calibration area with respect to the area covered by the species occurrences has been shown to affect model accuracy. However, existing assessments of the effect of data inadequacy and calibration size on model accuracy have predominately been conducted using empirical studies. These studies can give ambiguous results, since the data used to train and test the model can both be biased. These limitations were addressed by applying simulated data to assess how inadequate data coverage and the size of calibration area affect the accuracy of species distribution models generated by MaxEnt and BIOCLIM. The validity of four presence-only performance measures, Contrast Validation Index (CVI), Boyce index, AUC and AUCratio, was also assessed. CVI, AUC and AUCratio ranked the accuracy of univariate models correctly according to the true importance of their defining environmental variable, a desirable property of an accuracy measure. Contrastingly, Boyce index failed to rank the accuracy of univariate models correctly and a high percentage of irrelevant variables produced models with a high Boyce index. Inadequate data coverage and increased calibration area reduced model accuracy by reducing the correct identification of the dominant environmental determinant. BIOCLIM outperformed MaxEnt models in predicting the true distribution of simulated species with a symmetric dominant response. However, MaxEnt outperformed BIOCLIM in predicting the true distribution of simulated species with skew and linear dominant responses. Despite this, the standard performance measures consistently overestimated the performance of MaxEnt models and showed them as always having higher model accuracy than the BIOCLIM models. It has been acknowledged that research should be directed towards testing and improving species distribution modelling tools, particularly how to handle the inevitable bias and scarcity of species occurrence data. Simulated data, as demonstrated here, provides a powerful approach to comprehensively test the performance of modelling tools and to disentangle the effects of data properties and modelling options on model accuracy. This may be impossible to achieve using real-world data.
Testing main Amazonian rivers as barriers across time and space within widespread taxa

Present Amazonian diversity patterns can result from many different mechanisms and, consequently, the factors contributing to divergence across regions and/or taxa may differ. Nevertheless, the river‐barrier hypothesis is still widely invoked as a causal process in divergence of Amazonian species. Here we use model‐based phylogeographic analyses to test the extent to which major Amazonian rivers act similarly as barriers across time and space in two broadly distributed Amazonian taxa.
A deep learning method to detect network intrusion through flow‐based features

In this paper, we present a deep neural network model to enhance the intrusion detection performance. A deep learning architecture combining convolution neural network and long short‐term memory learns spatial‐temporal features of network flows automatically. Flow features are extracted from raw network traffic captures, flows are grouped, and the consecutive N flow records are transformed into a two‐dimensional array like an image. These constructed two‐dimensional feature vectors are normalized and forwarded to the deep learning model. Transformation of flow information assures deep learning in a computationally efficient manner. Overall, convolution neural network learns spatial features, and long short‐term memory learns temporal features from a sequence of network raw data packets. To maximize the detection performance of the deep neural network and to reach at the highest statistical metric values, we apply the tree‐structured Parzen estimator seeking the optimum parameters in the parameter hyper‐plane. Furthermore, we investigate the impact of flow status interval, flow window size, convolution filter size, and long short‐term memory units to the detection performance in terms of level in statistical metric values. The presented flow‐based intrusion method outperforms other publicly available methods, and it detects abnormal traffic with 99.09% accuracy and 0.0227 false alarm rate.
Genome-Wide Association Analyses Identify Variants in IRF4 Associated With Acute Myeloid Leukemia and Myelodysplastic Syndrome Susceptibility

The role of common variants in susceptibility to acute myeloid leukemia (AML), and myelodysplastic syndrome (MDS), a group of rare clonal hematologic disorders characterized by dysplastic hematopoiesis and high mortality, remains unclear. These diseases may have a shared molecular basis and identifying germline loci associated with the risk for their development could be important. We performed AML and MDS genome-wide association studies (GWAS) in European Americans from the DISCOVeRY-BMT study population (2309 cases and 2814 controls). Association analysis based on subsets (ASSET) was used to conduct a summary statistics SNP-based analysis of MDS and AML subtypes. For each AML and MDS case and control we used PrediXcan to estimate the component of gene expression determined by their genetic profile and correlate this imputed gene expression level with risk of developing disease in a transcriptome-wide association study (TWAS). We identified an increased risk for de novo AML and MDS (OR=1.38, 95% CI, 1.26-1.51, Pmeta=2.8×10−12) in patients carrying the T allele at rs12203592 in Interferon Regulatory Factor 4 (IRF4), a transcription factor which regulates myeloid and lymphoid hematopoietic differentiation. Variants in this gene are recognized to confer increased susceptibility to B-cell malignancies. Rs12203592 is <80 bp from an IRF4 transcription start site. Our TWAS analyses showed increased IRF4 gene expression is associated with increased risk of de novo AML and MDS (OR=3.90, 95% CI, 2.36-6.44, Pmeta =1.0×10−7). The identification of IRF4 by both GWAS and TWAS contributes valuable insight into the limited evidence of common variants associated with AML and MDS susceptibility.
Coupling Terrestrial Laser Scanning with 3D Fuel Biomass Sampling for Advancing Wildland Fuels Characterization

The spatial pattern of surface fuelbeds in fire-dependent ecosystems are rarely captured using long-standing fuel sampling methods. New techniques, both field sampling and remote sensing, that capture vegetation fuel type, biomass, and volume at super fine-scales (cm to dm) in three-dimensions (3D) are critical to advancing forest fuel and wildland fire science. This is particularly true for computational fluid dynamics fire behavior models that operate in 3D and have implications for wildland fire operations and fire effects research. This study describes the coupling of new 3D field sampling data with terrestrial laser scanning (TLS) data to infer fine-scale fuel mass in 3D. We found that there are strong relationships between fine-scale mass and TLS occupied volume, porosity, and surface area, which were used to develop fine-scale prediction equations using TLS across vegetative fuel types, namely grasses and shrubs. The application of this novel 3D sampling technique to high resolution TLS data in this study represents a major advancement in understanding fire-vegetation feedbacks in highly managed fire-dependent ecosystems.
Composition, density and biomass of fish community from the surf zone as a function of the lunar cycle at Miramar Beach in Cabedelo, Paraíba

ABSTRACT The influence of the moon cycles on the ichthyofauna has been little studied in the surf zone. In this study, the number of species, density and biomass were evaluated as a function of the moon. A total of 49 species distributed in 24 families were captured in two areas of Miramar beach. The mean density was significant high in the weaning and low in the new moon, while density and biomass together showed differences for areas. The most abundant species were Anchoa tricolor and Trachinotus falcatus (new moon), and Anchovia clupeoides showed significant differences in the waning moon. The RDA indicates that turbidity influenced significantly the presence of two species group. The group I were represented by Stellifer brasiliensis, Trachinotus goodei, A. clupeoides, Chilomycterus spinosus and Conodon nobilis that occurred on the waning and new phases in both areas, while the group II were represented by Polydactylus virginicus and Haemulopsis corvinaeformis in the full moon. The surf zones may also be strongly governed by the lunar phases. Therefore, the results found in this study, showed that the biological interactions between the species with turbidity and moon might explain the density and biomass variations for some species in the surf zone.
Identification of spatial compartments in tissue from in situ sequencing data

Spatial organization of tissue characterizes biological function, and spatially resolved gene expression has the power to reveal variations of features with high resolution. Here, we propose a novel graph-based in situ sequencing decoding approach that improves recall, enabling precise spatial gene expression analysis. We apply our method on in situ sequencing data from mouse brain sections, identify spatial compartments that correspond with known brain regions, and relate them with tissue morphology.