Miracle-dz/UniFAR-FTUs huggingface dataset:
Production and Biochemical Characterization of Dimeric Recombinant Gremlin-1

Gremlin-1 is a secreted cystine-knot protein that acts as an antagonist of bone morphogenetic proteins (BMPs), and as a ligand of heparin and the vascular endothelial growth factor receptor 2 (VEGFR2), thus regulating several physiological and pathological processes, including embryonic development, tissue fibrosis and cancer. Gremlin-1 exerts all these biological activities only in its homodimeric form. Here, we propose a multi-step approach for the expression and purification of homodimeric, fully active, histidine-tagged recombinant gremlin-1, using mammalian HEK293T cells. Ion metal affinity chromatography (IMAC) of crude supernatant followed by heparin-affinity chromatography enables obtaining a highly pure recombinant dimeric gremlin-1 protein, exhibiting both BMP antagonist and potent VEGFR2 agonist activities.
HMGB1-Mediated Neutrophil Extracellular Trap Formation Exacerbates Intestinal Ischemia/Reperfusion-Induced Acute Lung Injury

Key Points Activated neutrophil influx and NETosis contribute to intestinal I/R-induced ALI. Targeting NETosis and HMGB1 signaling effectively reduces intestinal I/R-induced ALI. Influx of activated neutrophils into the lungs is the histopathologic hallmark of acute lung injury (ALI) after intestinal ischemia/reperfusion (I/R). Neutrophils can release DNA and granular proteins to form cytotoxic neutrophil extracellular traps (NETs), which promotes bystander tissue injury. However, whether NETs are responsible for the remote ALI after intestinal I/R and the mechanisms underlying the dissemination of harmful gut-derived mediators to the lungs are unknown. In the C57BL/6J mouse intestinal I/R model, DNase I–mediated degradation and protein arginine deiminase 4 (PAD4) inhibitor–mediated inhibition of NET treatments reduced NET formation, tissue inflammation, and pathological injury in the lung. High-mobility group protein B1 (HMGB1) blocking prevented NET formation and protected against tissue inflammation, as well as reduced cell apoptosis and improved survival rate. Moreover, recombinant human HMGB1 administration further drives NETs and concurrent tissue toxic injury, which in turn can be reversed by neutrophil deletion via anti-Ly6G Ab i.p. injection. Furthermore, global MyD88 deficiency regulated NET formation and alleviated the development of ALI induced by intestinal I/R. Thus, HMGB1 released from necroptotic enterocytes caused ALI after intestinal I/R by inducing NET formation. Targeting NETosis and the HMGB1 pathway might extend effective therapeutic strategies to minimize intestinal I/R-induced ALI.
Proteomic analysis of metabolic pathways supports chloroplast–mitochondria cross‐talk in a Cu‐limited diatom

Abstract Diatoms are one of the most successful phytoplankton groups in our oceans, being responsible for over 20% of the Earth's photosynthetic productivity. Their chimeric genomes have genes derived from red algae, green algae, bacteria, and heterotrophs, resulting in multiple isoenzymes targeted to different cellular compartments with the potential for differential regulation under nutrient limitation. The resulting interactions between metabolic pathways are not yet fully understood. We previously showed how acclimation to Cu limitation enhanced susceptibility to overreduction of the photosynthetic electron transport chain and its reorganization to favor photoprotection over light harvesting in the oceanic diatom Thalassiosira oceanica (Hippmann et al., 2017, 10.1371/journal.pone.0181753). In order to gain a better understanding of the overall metabolic changes that help alleviate the stress of Cu limitation, we have further analyzed the comprehensive proteomic datasets generated in that study to identify differentially expressed proteins involved in carbon, nitrogen, and oxidative stress‐related metabolic pathways. Metabolic pathway analysis showed integrated responses to Cu limitation. The upregulation of ferredoxin (Fdx) was correlated with upregulation of plastidial Fdx‐dependent isoenzymes involved in nitrogen assimilation as well as enzymes involved in glutathione synthesis, thus suggesting an integration of nitrogen uptake and metabolism with photosynthesis and oxidative stress resistance. The differential expression of glycolytic isoenzymes located in the chloroplast and mitochondria may enable them to channel both excess electrons and/or ATP between these compartments. An additional support for chloroplast–mitochondrial cross‐talk is the increased expression of chloroplast and mitochondrial proteins involved in the proposed malate shunt under Cu limitation.
Extended incremental non-linear control allocation (XINCA) for quadplanes

Hybrid UAVs have gained a lot of interest for their combined vertical take-off & landing (VTOL) and efficient forward flight capabilities. But their control is facing challenges in over-actuation and conflicting requirements depending on the flight phase which can easily lead to actuator saturation. Incremental Non-linear Control Allocation (INCA) has been proposed to solve the platform’s control allocation problem in the case of saturation or over-actuation by minimizing a set of objective functions. This work demonstrates INCA on quadplanes, an in-plane combination between a quadrotor and a conventional fixed-wing, and proposes an extension to control the outer loop. The novel controller is called Extended INCA (XINCA) and adds the wing orientation as a force-generating actuator in the outerloop control optimization. This leads to a single controller for all flight phases that avoids placing the wing at negative angles of attack and minimizes the load on hover motors. XINCA has low dependence on accurate vehicle models and requires only several optimization parameters. Flight simulations and experimental flights are performed to demonstrate the performance.
Çözücü ve Isıl İşlem Sürecinin MoS2 İnce Filmlerinin Yapısal Özelliklerine Etkisinin İncelenmesi

In recent years, transition metal dichalcogenides (TMDCs) have become one of the most studied material groups due to their unique physical and chemical properties. The TMDCs are frequently used in optoelectronic applications, hydrogen evolution reactions, energy storage systems, solar cells, and radar absorbing systems. In this study, the structural properties of MoS 2 thin films, belonging to one of the TMDCs group, produced by using different solvents and heat treatment processes were investigated. Thin films were produced by using the sol-gel spin coating technique. The crystallization of the films was ensured at different heat treatment temperature values under a vacuum atmosphere by introducing N 2 gas flow. The effects of the heat treatment temperature and chemical solvent were evaluated by the structural characterizations techniques. Within this scope, the X-ray diffraction method (XRD), Raman scattering, and scanning electron microscope (SEM) were used to investigate the structural properties of films.
HIGH RESOLUTION IMAGE PROCESSING AND LAND COVER CLASSIFICATION FOR HYDRO- GEOMORPHOLOGICAL HIGH-RISK AREA MONITORING

High-resolution image processing for land surface monitoring is fundamental to analyze the impact ofdifferent geomorphological processes on Earth surface for different climate change scenarios. In thiscontext, photogrammetry is one of the most reliable techniques to generate high-resolutiontopographic data, being key to territorial mapping and change detection analysis of landforms inhydro-geomorphological high-risk areas. An important issue arises as soon as the main goal is toconduct analyses over extended areas of the Earth surface (such as fluvial systems) in a short time,since the need to capture large datasets to develop detailed topographic models may limit thephotogrammetric process, due to the high demand of high-performance hardware. In order toinvestigate the best set up of computing resources for these very peculiar tasks, a study of theperformance of a photogrammetric workflow based on a FOSS (Free Open-Source Software) SfM(Structure from Motion) algorithm using different cluster configurations was conducted, leveragingthe computing power of ReCaS-Bari data center infrastructure, which hosts several services such asHTC, HPC, IaaS, PaaS. Exploiting the high-computing resources available at clusters and choosingspecific set up for the workflow steps, an important reduction of several hours in the processing timewas recorded, especially compared to classic photogrammetric programs processed on a singleworkstation with commercial softwares. The high quality of the image details can be used for landcover classification and preliminary change detection studies using Machine Learning techniques. Asubset of the datasets used for the workflow implementation has been considered to test theperformance of different Convolutional Neural Networks, using progressively more complex layersequences, data augmentation and callback functions for training the models. All the results are givenin terms of model accuracy and loss and performance evaluation.
Exploring the Physiological and Psychological Effects of Digital Shinrin-Yoku and Its Characteristics as a Restorative Environment

This study investigated the physiological and psychological therapeutic effects of a digital Shinrin-yoku environment constructed indoors in an urban facility as well as the characteristics of the environment that contribute to restorativeness (restorative traits). We measured the fluctuations in the physical and mental states of 25 subjects by obtaining both before–after measurements and continuous measurements while exposed to a digital Shinrin-yoku environment that reproduced visual, auditory, and olfactory elements. The results demonstrated that the parasympathetic nerve activity was significantly increased and that the heart rate was significantly decreased during the exposure compared with that during the resting state. As for mood, five of the six Profile of Mood States (POMS) scales (“Tension–Anxiety,” “Depression,” “Anger–Hostility,” “Fatigue,” and “Confusion”) were significantly decreased after the experience. In addition, psychological restorative effects were also confirmed, with a significant decrease in “negative affect” (measured using the Positive and Negative Affect Schedule (PANAS)) and a significant increase in the sense of restorativeness (Restorative Outcome Scale (ROS)) after the experience. In contrast, comparing the digital Shinrin-yoku environment with the actual forest environment and the urban environment using POMS, PANAS, ROS, and Perceived Restorativeness Scale (PRS), the psychological effects and environmental traits of the digital Shinrin-yoku were found to be considerably similar to those of the actual forest environment.
SARS-CoV-2 impairs interferon production via NSP2-induced repression of mRNA translation

Viruses evade the innate immune response by suppressing the production or activity of cytokines such as type I interferons (IFNs). Here we report the discovery of a novel mechanism by which the SARS-CoV-2 virus co-opts an intrinsic cellular machinery to suppress the production of the key immunostimulatory cytokine IFN-β. We reveal that the SARS-CoV-2 encoded Non-Structural Protein 2 (NSP2) directly interacts with the cellular GIGYF2 protein. This interaction enhances the binding of GIGYF2 to the mRNA cap-binding protein 4EHP, thereby repressing the translation of the Ifnb1 mRNA. Depletion of GIGYF2 or 4EHP significantly enhances IFN-β production, leading to reduced viral infection. Our findings reveal a new target for rescuing the antiviral innate immune response to SARS-CoV-2 and other RNA viruses.
Vanadium dioxide metasurfaces structures with infrared radiation protection properties

This paper presents a laser protection idea to form a two-dimensional subwavelength metasurfaces structure with phasechange vanadium dioxide (VO2) material. By using the phase change characteristics of VO2, the signal light can be focused to the infrared focal plane at room temperature, and VO2 undergoes a phase change under the action of a strong laser, which causes the spot on the focal plane to diverge, reducing the light intensity and energy density to protect the focal plane. The final imaging spot diameter of the metasurfaces designed in this paper is 4. 4μm, which can intercept 76% of the incident energy from the outside after the phase change.
Method of the Modeling and Abstraction of Typical Thermal Experiment Unit for Sub-Critical Fuel Components

The sub-critical module-fuel component is the core component of the sub-critical blanket in fusion–fission hybrid energy system. The thermal safety experiment for module-fuel component is the foundation and necessary step of obtaining thermal design principle, developing structure design and safety analysis. In this paper, the necessary experiment modeling technique of thermal safety experiment is researched. The analysis for the particular thermal-hydraulics structure is developed. The related calculation, by computational fluid dynamic(CFD) method, is developed to confirm the parameter of object. The structure abstraction of typical thermal experiment unit is obtained. This work supplies the basis of following experiment body design.
Novel Fault Diagnosis Approach of Power Grid Using Data Fusion

When fault happens in the power grid,the diagnosis result is uncertain sometimes because of the mal-operation and miss-operation. Firstly,the power gird diagnosis based on data fusion is proposed in this paper. Then,fused the digital and analogue data,the Petri fault degree is obtained by fuzzy Petri nets. By Hilbert-Huang transform(HHT),the amplitude fault degree,the frequency fault degree and the energy fault degree are obtained. The D-S evidence theory is employed to fuse the degrees. Finally,the research is proved to be available by the application of some cases in which the uncertain factors could be eliminated and thus,the accuracy of the fault diagnosis could be improved.
Optimising partner notification outcomes for bacterial sexually transmitted infections: a deliberative process and consensus, United Kingdom, 2019

Partner notification (PN) is an essential element of sexually transmitted infection (STI) control. It enables identification, treatment and advice for sexual contacts who may benefit from additional preventive interventions such as HIV pre- and post-exposure prophylaxis. PN is most effective in reducing STI transmission when it reaches individuals who are most likely to have an STI and to engage in sexual behaviour that facilitates STI transmission, including having multiple and/or new sex partners. Outcomes of PN practice need to be measurable in order to inform standards. They need to address all five stages in the cascade of care: elicitation of partners, establishing contactable partners, notification, testing and treatment. In the United Kingdom, established outcome measures cover only the first three stages and do not take into account the type of sexual partnership. We report an evidence-based process to develop new PN outcomes and inform standards of care. We undertook a systematic literature review, evaluation of published information on types of sexual partnership and a modified Delphi process to reach consensus. We propose six new PN outcome measures at five stages of the cascade, including stratification by sex partnership type. Our framework for PN outcome measurement has potential to contribute in other domains, including Covid-19 contact tracing.
Adaptive Algorithm on Break-variable Detection in Line Protection

For raditional break-variable detecting method is easy to be influenced by grid frequency and its improved algorithm is hard to meet the relay speed requirements,the paper proposes a kind of new adaptive area break-variable algorithm.The algorithm takes the difference of current integral in each half cycle as the criteria to judge whether the break-variable occurred.Its sampling frequency could track the that of power system adaptively and the area width could be adjusted with the current amplitude adaptively.The line protection device based on this algorithm has passed the dynamic simulation examination in National Relay Protection and Automation Equipment Quality Supervision and Inspection Center.The experiment shows that the starting element can make fast action when break-variable occurred.It is better in interference ability,high in reliability and could detect break-variable rapidly and accurately.The experiment result shows that the algorithm is feasible and reasonable.
Understanding nutritive need in Harmonia axyridis larvae: Insights from nutritional geometry

The multicolored Asian lady beetle, Harmonia axyridis (Pallas) (Coleoptera: Coccinellidae), is an important natural enemy in agricultural ecosystems. In spite of being a carnivore consuming protein‐rich preys, the lady beetles often consume carbohydrate‐rich food like nectar or honeydew. However, most studies on nutrition regulation of carnivores mainly focus on protein and lipid, two major macronutrients in preys. In this study, nutrition regulation of protein and carbohydrate has been investigated in the 4th instar larvae of H. axyridis using Geometric Framework. We provided the insects two pairs of foods, one a protein‐biased one and the second carbohydrate‐biased, to determine the intake target. We then confined them to nutritionally imbalanced foods to examine how they regulated food intake to achieve maximal performance. The larvae performed well on the 2 foods that containing the closest P : C ratios to the intake target, but, surprisingly, the lipid content was much lower than that in the choice experiment. The lady beetles seemed to maintain the optimal lipid content by consuming carbohydrate‐rich food. Moreover, consuming the carbohydrate‐rich food was less metabolically expensive than the protein‐rich food. Therefore, switching behavior between plant and animal foods actually reflects their nutritive needs. These findings extended our understanding of predator forage behavior and its influence on food web in ecosystems, and shed light on the role of agri‐environment schemes in meeting the nutritional need of predators in field.
zipper

ENSG00000007908 -5.65 1.99E-70 SELE selectin E ENSG00000162692 -5.33 1.97E-45 VCAM1 vascular cell adhesion molecule 1 ENSG00000100311 -4.23 8.29E-246 PDGFB platelet-derived growth factor beta polypeptide ENSG00000143869 -4.23 9.81E-201 GDF7 growth differentiation factor 7 ENSG00000108691 -3.88 1.66E-134 CCL2 chemokine (C-C motif) ligand 2 ENSG00000090339 -3.76 0.00E+00 ICAM1 intercellular adhesion molecule 1 ENSG00000111341 -3.74 3.84E-78 MGP matrix Gla protein ENSG00000125378 -3.59 7.84E-144 BMP4 bone morphogenetic protein 4 ENSG00000049540 -3.58 2.76E-26 ELN elastin ENSG00000168542 -3.57 4.46E-25 COL3A1 collagen; type III; alpha 1 ENSG00000017427 -3.54 4.09E-24 IGF1 insulin like growth factor 1
Finite Element Analysis of thin plates clamped on the rim of different geometric forms. Part II: The Absolute and Relative Variation of Natural Frequencies

In this paper, according to the natural frequencies resulted from the simulation for 30 vibration mode shapes of rectangular, square, trapeze and parallelogram plates that are analyzed with the SolidWorks program, the absolute respectively the relative variation has been obtained for thin clamped plates with the same area. The absolute and relative variation of natural frequencies was made for 6 possible cases of the 4 type of plates, namely: rectangle-square, trapeze-rectangle, trapeze-square, parallelogram-rectangle, parallelogram-square and trapeze-parallelogram.
Capacity building through project based learning in Bayesian statistics

Outcome-based education requires statistics education in the 21st century to be structured holistically by allowing the students to work with real life data along with visualization, computation, and learning outputs. The new K-12 curriculum resulted to a chain reaction in the Statistics undergraduate program by including alternative statistical frameworks such as Bayesian statistics. This paper focuses on project-based learning approach on designing learning outputs for undergraduate and graduate students in Bayesian statistics. The stages of project-based learning in completing these Bayesian learning outputs have helped in building the capacities of the students to understand the essential concepts in Bayesian inference and do computations using software. Some of the learning outputs are cited. Insights are helpful in making the syllabus of Bayesian Statistics and Inference of undergraduate Statistics program. Project based learning incapacitates the students to do Statistics research in an organized manner and make decisions based on data.
Vessel Wall Magnetic Resonance Imaging in Cerebrovascular Diseases

Cerebrovascular diseases are a leading cause of disability and death worldwide. The definition of stroke etiology is mandatory to predict outcome and guide therapeutic decisions. The diagnosis of pathological processes involving intracranial arteries is especially challenging, and the visualization of intracranial arteries’ vessel walls is not possible with routine imaging techniques. Vessel wall magnetic resonance imaging (VW-MRI) uses high-resolution, multiparametric MRI sequences to directly visualize intracranial arteries walls and their pathological alterations, allowing a better characterization of their pathology. VW-MRI demonstrated a wide range of clinical applications in acute cerebrovascular disease. Above all, it can be of great utility in the differential diagnosis of atherosclerotic and non-atherosclerotic intracranial vasculopathies. Additionally, it can be useful in the risk stratification of intracranial atherosclerotic lesions and to assess the risk of rupture of intracranial aneurysms. Recent advances in MRI technology made it more available, but larger studies are still needed to maximize its use in daily clinical practice.
Observer-based consensus control and fault detection for multi-agent systems

A robust consensus control and fault detection algorithm is proposed for a class of nonlinear multi-agent systems subject to unknown external disturbances.First,an unknown input nonlinear observer is designed for each agent.Then,a robust consensus control protocol is presented to achieve the state consensus of the multi-agent systems by applying the estimated information of the nonlinear unknown input observers.The desired disturbance rejection criterion is guaranteed by the proposed control protocol.Thirdly,an adaptive threshold is derived and a fault detection approach based on adaptive threshold is proposed to detect the fault of each agent.The fault detection can be implemented by each agent in a fully distributed fashion.Finally,the proposed method is applied to the networked simple pendulums which are driven by dc motors.Simulation results are provided to validate the effectiveness of the proposed consensus control and fault detection scheme.
Adaptive AGC strategy based on statistical property of CPS

The adaptive AGC strategy based on the statistical property of CPS is presented.The structure of adaptive control system and the design of CPS / DCS controller are introduced and the adjustment rules of adaptive CPS control parameters varying according to the power grid structure,operational mode and actual requirement are detailed.The design of adaptive AGC strategy is based on the CPS control rules of NARI,automatically sets its parameters and refers to the optimal control methods based on economic and indicative performances,which can be easily implemented on current AGC systems.Study shows that the proposed strategy effectively mitigates the AGC pressure of power plants while the CPS compliance is ensured.