Miracle-dz/UniFAR-FTUs huggingface dataset:
The Rise and Fall of μ Velorum: A Remarkable Flare on a Yellow Giant Star Observed with the Extreme Ultraviolet Explorer

The close visual double μ Velorum (HD 93497; G6 III+dF) consists of a yellow giant and a fainter companion currently 2'' apart. Recently μ Vel was the source of a large flare recorded by the Extreme Ultraviolet Explorer. The long 1.5 day decay phase was like the extremes seen on hyperactive RS CVn-type binaries. The primary, μ Vel A is a 3 M☉ star, in the "rapid braking zone" redward of G0 III. Yellow giants are not commonly reported as flare stars, perhaps because the first-crossers are relatively rare and not well represented in the observational samples. The secondary star is classified G2 V, but the 1700 Å energy distribution places it earlier on the main sequence, probably F4 or F5 V, in a class also not usually known for coronal variability. The long duration of the μ Vel event suggests that it occurred in a significantly elongated structure of moderate density, ne ≲ 109 cm-3. If it was a magnetic plasmoid, like a coronal mass ejection on the Sun, then such events might play a role in shedding angular momentum from active evolved stars. The associated spin-down could control the activity survival time of red giants (in later stages of evolution than the first-crosser μ Vel) whose dynamos were rejunvenated by dredge-up of angular momentum from the interior, or more exotic sources, such as cannibalism of close-in substellar companions during the first or second ascent.
Waveform-Logmel Dual Stream Fusion Network for Sound Event Detection

Although Convolutional Recurrent Neural Network (CRNN) has proven to be an effective method for sound event detection, problems still exist. The feature extractor cannot effectively extract and fuse audio deep features with different semantics. Thus hard to cope with the complex sound scenes in real environments. To address these issues, we present a novel framework with a dual-stream network with a feature fusion module. More precisely, we first extract the deep features of the Logmel spectrogram and the raw waveform separately. Then, we use Selective Feature module to fuse the features of the dual streams. The module use channel attention mechanism to assign weights to each channel of the fused feature map, forcing the model to focus on important sound features while ignoring unrelated feature. Experiments on the DCASE 2022 Task 4 validation set demonstrate the effectiveness of our model. Ensembling this system, the PSDS-scenario1 and 2 of 37.9% and 62.3% outperform the baseline system of 33.3% and 53.6%.
10 Years of Hurricane Synoptic Surveillance (1997-2006)

Abstract In 1997, the National Hurricane Center and the Hurricane Research Division began operational synoptic surveillance missions with the Gulfstream IV-SP jet aircraft to improve the numerical guidance for hurricanes that threaten the continental United States, Puerto Rico, the U.S. Virgin Islands, and Hawaii. During the first 10 yr, 176 such missions were conducted. Global Positioning System dropwindsondes were released from the aircraft at 150–200-km intervals along the flight track in the environment of each tropical cyclone to obtain wind, temperature, and humidity profiles from flight level (about 150 hPa) to the surface. The observations were processed and formatted aboard the aircraft and sent to the National Centers for Environmental Prediction and the Global Telecommunications System to be ingested into the Global Forecast System, which serves as initial and boundary conditions for regional numerical models that also forecast tropical cyclone track and intensity. The results of an observing s.
The Impact of Software Used and the Type of Target Protein on Molecular Docking Accuracy

The modern development of computer technology and different in silico methods have had an increasing impact on the discovery and development of new drugs. Different molecular docking techniques most widely used in silico methods in drug discovery. Currently, the time and financial costs for the initial hit identification can be significantly reduced due to the ability to perform high-throughput virtual screening of large compound libraries in a short time. However, the selection of potential hit compounds still remains more of a random process, because there is still no consensus on what the binding energy and ligand efficiency (LE) of a potentially active compound should be. In the best cases, only 20–30% of compounds identified by molecular docking are active in biological tests. In this work, we evaluated the impact of the docking software used as well as the type of the target protein on the molecular docking results and their accuracy using an example of the three most popular programs and five target proteins related to neurodegenerative diseases. In addition, we attempted to determine the “reliable range” of the binding energy and LE that would allow selecting compounds with biological activity in the desired concentration range.
Antenna impedance measurements in a magnetized plasma. II. Dipole antenna

This paper presents experimental impedance measurements of a dipole antenna immersed in a magnetized plasma. The impedance was derived from the magnitude and phase of the reflected power using a network analyzer over a frequency range of 1MHz–1GHz. The plasma density was varied between 107and1010cm−3 in weakly (ωce ωpe) magnetized plasmas in the Space Physics Simulation Chamber at the Naval Research Laboratory. Over this range of plasma conditions the wavelength in the plasma varies from the short dipole limit (λ≫L) to the long dipole limit (λ∼L). As with previous impedance measurements, there are two resonant frequencies observed as frequencies where the impedance of the antenna is real. Measurements have indicated that in the short dipole limit the majority of the power deposition takes place at the lower resonance frequency which lies between the cyclotron frequency and the upper hybrid frequency. These measured curves agree very well with the analytic theory for a short dipole i.
Fur, Fin, and Feather: Management of Animal Interactions in Australian Residential Aged Care Facilities

Simple Summary Animals are seen frequently in Australian Residential Aged Care Facilities (RACF). Research has demonstrated that there are risks to residents and the animals involved, with few policies or guidelines to assist managers in developing RACF animal policies. Via survey and interview, we asked RACF managers how they managed the interactions between residents and animals in their facilities. While the majority of RACFs reported some level of policy, coverage was limited, potentially risking animal and/or resident safety. For example, many facilities had no policy around handwashing when handling animals, and many facilities allowed visitors to bring family pets onsite but had no rules to guide these visits. The results of this study suggest that RACF managers need access to guidelines for the inclusion of animals in their facilities to keep residents and animals safe. Abstract Animal-assisted interventions (AAI) have been occurring in Australian Residential Aged Care Facilities (RACF) for more than 40 years and may relieve loneliness and improve quality of life. The presence of animals in RACF poses an inherent risk to residents and the animals involved. Little is known about the policies and guidelines for including animals in the Australian RACF. We anticipated that most RACFs would have some policies, but they may lack the detail necessary to keep humans and animals safe. Using an adapted survey, we surveyed and interviewed a small but representative sample of Australian RACF managers. The results demonstrated that RACF did have animal policies; however, the content regarding the need for hand washing, infection prevention, and animal welfare was lacking. Including unregulated family pets in RACF was an unexpected additional risk factor identified during data analysis. There is a need for national guidelines tied to the national aged care policy, which includes training and educational resources for RACF and AAI providers.
Mutual Support and Promotion: Learning Structure Compensation and Context Completion for Low-Light Vision

In recent years, visual perception tasks (e.g., object detection) in harsh scenes (e.g., low-light scenes) have received extensive attention due to their importance in various practical applications (e.g., autonomous driving). However, when addressing the above tasks, existing works are often too simplistic and straightforward to characterize different types of features, and often only focus on a single task while neglecting the performance of multiple tasks. To break the limitations of existing methods, this paper proposes a Structure Compensation and Context Completion Network (SC3N) for solving perception tasks in low-light scenes. Specifically, we first construct an object detection network and a self-supervised low-light image enhancement network to jointly extract various task-related features while meeting the task requirements. Furthermore, in order to reasonably utilize the effective information held by complex and different kinds of features, we design a structure compensation module and a context completion module to realize the information exchange between different tasks. Through the proposed bidirectional information interaction framework, the method could realize the mutual transfer and dynamic guidance of feature-level structural information and feature-level context information, thereby enabling the network to jointly improve low-light performance low-light images enhancement and detection. Finally, extensive comparative experiments fully verify the superiority of the proposed method compared with other state-of-the-art methods in both enhancement and detection. In addition, we also design a series of ablation analyses for each module to verify the effectiveness of the proposed method.
Melatonin as a Potential Approach to Anxiety Treatment

Anxiety disorders are the most common mental diseases. Anxiety and the associated physical symptoms may disturb social and occupational life and increase the risk of somatic diseases. The pathophysiology of anxiety development is complex and involves alterations in stress hormone production, neurosignaling pathways or free radical production. The various manifestations of anxiety, its complex pathophysiological background and the side effects of available treatments underlie the quest for constantly seeking therapies for these conditions. Melatonin, an indolamine produced in the pineal gland and released into the blood on a nightly basis, has been demonstrated to exert anxiolytic action in animal experiments and different clinical conditions. This hormone influences a number of physiological actions either via specific melatonin receptors or by receptor-independent pleiotropic effects. The underlying pathomechanism of melatonin’s benefit in anxiety may reside in its sympatholytic action, interaction with the renin–angiotensin and glucocorticoid systems, modulation of interneuronal signaling and its extraordinary antioxidant and radical scavenging nature. Of importance, the concentration of this indolamine is significantly higher in cerebrospinal fluid than in the blood. Thus, ensuring sufficient melatonin production by reducing light pollution, which suppresses melatonin levels, may represent an endogenous neuroprotective and anxiolytic treatment. Since melatonin is freely available, economically undemanding and has limited side effects, it may be considered an additional or alternative treatment for various conditions associated with anxiety.
Underlying Causes of Myocardial Infarction with Nonobstructive Coronary Arteries: Optical Coherence Tomography and Cardiac Magnetic Resonance Imaging Pilot Study

Background: Scientific statements recommend multimodality imaging in myocardial infarction with non-obstructive coronary arteries (MINOCA) to define the underlying cause. Aim: We evaluated the diagnostic yield of intravascular optical coherence tomography (OCT) and cardiac magnetic resonance (CMR) in the MINOCA setting. Methods: In this prospective, single center, observational pilot study, we enrolled patients with MINOCA without previous coronary interventions. All patients underwent three vessel OCT, followed by CMR. Imaging results were combined to determine the mechanism of MINOCA, when possible. Results: We enrolled 10 patients in this pilot study. Women constituted 50% of the analyzed population. The mean age of patients was 52 years. ST-segment elevation was found in 30% of patients. A possible culprit lesion was identified by OCT in 70% of participants, most commonly plaque rupture or erosion. An ischemic pattern of CMR abnormalities was identified in 70% of participants. Myocarditis and Tako-Tsubo were identified in 30%. A cause of MINOCA was identified in all patients using multimodality imaging, while using OCT alone identification occurred in only 70% of patients. Conclusion: In this pilot study, multimodality imaging with OCT and CMR identified potential mechanisms in all patients with a diagnosis of MINOCA, and it has the potential to guide medical therapy for secondary prevention.
Secondary Metabolites From the Grasshopper-Derived Entomopathogenic Fungus Aspergillus Tamarii NL3 and Their Biological Activities

Chromatographic purification of the ethyl acetate extract of the entomopathogenic fungus Aspergillus tamarii NL3 culture broth led to the isolation of griseofulvin (1), isogriseofulvin (2), cytochalasin J (3), solamargine (4), and solasonine (5). The chemical structures of these compounds were identified by HRESIMS and NMR spectra, as well as by comparison with literature data. This is the first report on the isolation of 1-4 from the Aspergillus genus and compound 5 from A tamarii. Compounds 1 and 2 exhibited antifungal activity against the reference fungi with MICs of 16 to 128 µg/mL. Compound 3 displayed weak antimicrobial activity against most of the tested microorganisms with MICs ≥ 128 µg/mL, except for Bacillus subtilis and Aspergillus niger with MICs of 64 µg/mL. Compounds 4 and 5 showed activity against a wide spectrum of the reference microorganisms with MICs of 16 to 128 µg/mL but showed stronger antifungal than antibacterial activity. Furthermore, all isolates exhibited weak ABTS and DPPH scavenging activities with scavenging rates of 18.92% to 32.64% and 24.62% to 31.06%, respectively, at the concentration of 100 µg/mL.
ON THE CLASSICAL SOLUTION OF NONLINEAR ELLIPTIC EQUATIONS OF SECOND ORDER

The Dirichlet problem in , on , is considered for nonlinear elliptic equations, including Bellman equations with coefficients in the Holder space . It is proved that if 0$ SRC=http://ej.iop. org/images/0025-5726/33/3/A07/tex_im_858_img6. gif/> is sufficiently small, then this problem is solvable in . If in addition and , then the solution belongs to . Bibliography: 18 titles.
Feed Supplemented with Aronia melanocarpa (AM) Relieves the Oxidative Stress Caused by Ovulation in Peak Laying Hens and Increases the Content of Yolk Precursors

Simple Summary The current work evaluated the protective effect of Aronia melanocarpa(AM ) on the liver and ovary of laying hens during the peak laying period and the related mechanisms. In this study, we observed the morphology and histology of liver and ovary and found that AM can alleviate the damage caused by oxidative stress. Serum biochemical parameters and expression abundance of key gene proteins were measured at 33 weeks of age. AM can activate the kelch-like ECH-associated protein 1 (Keap1)/ nuclear factor erythroid-2 related factor 2 (Nrf2) signal pathway, increase the content of antioxidant enzymes, increasing the hormone content, thereby improving the yolk synthesis capacity, and ultimately improving the production performance and egg quality of peak laying hens. Abstract The continuous ovulation of laying hens during the peak period is likely to cause oxidative stress, resulting in a reduction in the laying cycle over time. The aim of this study was to evaluate the antioxidant effects of Aronia melanocarpa (AM) in the diet and its effect on the yolk precursor content caused by ovulation in laying hens during the peak period. A total of 300 25-week-old Roman brown laying hens were randomly divided into five groups with six replicates in each group, 10 in each replicate. The control group was fed a basal diet, the positive control group was fed a Vitamin C (VC) plus basal diet, and the experimental group was fed 1%, 4%, and 7% doses of AM plus diet according to the principle of energy and nitrogen requirements, which lasted eight weeks. At the end of the study, the egg quality, biochemical, and antioxidant markers, as well as mRNA and protein expressions, were evaluated to determine the potential signaling pathways involved. Results showed that the addition of AM to the feed increased the weight of laying hens at the peak of egg production and improved egg quality. The biochemical markers, as well as the antioxidant parameters in the serum, liver, and ovarian tissues, were ameliorated. The gene and protein expression of recombinant kelch-like ECH-associated protein 1 (Keap1) in the liver and ovarian tissues was decreased, while nuclear factor erythroid-2 related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) expression was increased. The feed supplemented with AM also increased the estrogen contents and lipid parameters, as well as the gene and protein expressions related to the yolk precursor. Feed supplemented with AM could improve the egg quality and the oxidative stress caused by the ovulation process of laying hens during the peak egg production period by activating the Keap1/Nrf2 signaling pathway. These results suggest that the feed supplemented with 1% AM and 4% AM can improve egg production in peak laying hens.
Energy Consumption Control Method for Oven based on DDPG

Oven equipment wastes a lot of energy to ensure the process and production requirements during car manufacturing. To solve this problem, this paper proposes an energy consumption control method for oven based on DDPG. This paper collects equipment data in real time by IoT technology; To solve the problems of abnormal data and inconsistent dimensions, data cleaning is applied; Then, the key features of energy consumption are extracted by integrated feature selection and dimension reduction algorithm to improve the upper limit of the model; After that, this paper creates an energy consumption reward function to evaluate energy consumption effect of parameter setting; Finally, the accuracy of the model can be improved by setting appropriate state space and action space of the model, building the network structure of the model and adjusting the super parameters; The energy consumption of oven can be controlled by this model and experiments show that the algorithm can reduce about 18% energy consumption of oven with process requirements, which the energy saving effect is good.
Resolution sensitivity of momentum‐exchange and immersed boundary methods for solid–fluid interaction in the lattice Boltzmann method

In the lattice Boltzmann method (LBM), the mechanism of fluid–solid interaction can be effectively captured by appropriately enforcing the no‐slip conditions in shear direction, and bounce‐back of the non‐equilibrium distribution portion in the normal direction at fluid–solid interfaces. Among various solid–fluid interaction schemes being proposed for LBM in recent decades, two simple fluid–solid interaction methods—the momentum exchange algorithm (MEA) and the immersed boundary scheme (IBS)—were developed based on the above concept. In this paper, MEA and IBS are implemented in a D2Q9 LBGK system and applied to measure the wall correction factors of drag force upon a stationary circular particle midway in the Poiseuille channel flow at very low Reynolds number and drag coefficients at low to moderate Reynolds numbers. MEA and IBS are also employed to compare the fluid‐induced torque over the cylinder in the Taylor–Couette flow, and the steady velocity of a particle settling under the influence of gravity inside a tube. The above experiments show that IBS seems to be more accurate and less demanding on lattice resolution. Copyright © 2010 John Wiley & Sons, Ltd.
On the Method of Approximation by Families of Linear Polynomial Operators

It is shown that best approximation by trigonometric polynomials is achieved in average by families of linear polynomial operators in the Lp-metric for all p, 0 < p ≤ ∞. This is compared with approximation by Fourier means and interpolation means which is restricted to 1 ≤ p ≤ ∞ and p = ∞, respectively.
The conditioning of social networking sites in the formation of migratory chains of unaccompanied foreign minors

The relational uprooting faced by young unaccompanied minors, when they undertake a migratory process, it places them in a situation of extreme vulnerability. Timeshare in the Center for Minors offered relationships between themselves, which are later maintained and reflected on social networking sites. The content that can be shared on social networking sites could condition the subsequent migratory itinerary travel and the migratory chains that are formed. In this study, the profiles on social networking sites of 51 unaccompanied minors were analyzed one year after having passed through a Center for Minors located in Malaga (Spain). Through social networks analysis, netnography and certain algorithms for community detection, cohesion and emotion analysis, the connectedness and interaction patterns shown by these young people on social networking sites (Facebook) will be analyzed, identifying leaderships and detecting communities that influence the formation of migratory chains. The results show how the patterns of connectedness, interaction and leadership reflect migratory chains.
Rapid Characterisation of Stakeholder Networks in Three Catchments Reveals Contrasting Land-Water Management Issues

Catchments are socio-ecological systems integrating land, water and people with diverse roles and views. Characterising stakeholder networks and their levels of influence and interaction within catchments can help deliver more effective land and water management. In this study, we combined stakeholder analysis and social network methods to provide a novel stakeholder-mapping tool capable of identifying interactions among the land and water management communities across three contrasting study catchments. The overarching aim was to characterise the influence of different stakeholders involved in catchment management based on the perceptions of participants from four key stakeholder groups (Environmental Regulators, Water Industry Practitioners, the Farm Advisor Community, and Academics). A total of 43 participants identified 28 types of specific catchment management stakeholder groups with either core or peripheral importance to our three case study catchments. Participants contributed 490 individual scores relating to the perceived influence of these different stakeholder groups and categorised whether this influence was positive, negative or neutral for the management of catchment resources. Local Government, Farmers and Environmental Regulators were perceived to have the greatest level of influence. Social network analysis further determined which stakeholders were most commonly connected in all of the study catchments and hence formed the core of stakeholder networks in each catchment. Comparing outputs from the analysis of three contrasting river catchments, as well as between participants from four key stakeholder groups allowed identification of which stakeholders were more central to the catchment management networks. Such analyses could help facilitate effective communication within land and water management stakeholder networks by targeting highly connected opinion leaders or promoting peer learning via distinct catchment subgroups.