Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatially resolved kinematics, galactic wind, and quenching of star formation in the luminous infrared galaxy IRAS F11506-3851

We present a multi-wavelength integral field spectroscopic (IFS) study of the low-z luminous infrared galaxy IRAS F11506-3851 (ESO 320-G030) on the basis of the moderate spectral resolution observations (R 3400 4000) taken with the VIMOS and SINFONI instruments at the ESO VLT. The morphology and the 2D kinematics of the gaseous (neutral and ionized) and stellar components have been mapped in the central regions (<3 kpc) using the NaD 5890, 5896 A absorption doublet, the H 6563 A line, and the near-IR CO(2‐0) 2.293 m and CO(3‐1) 2.322 m bands. The kinematics of the ionized gas and the stars are dominated by rotation, with large observed velocity amplitudes ( V(H ) = 203 4 km s 1 ; V(CO) = 188 11 km s 1 , respectively) and centrally peaked velocity dispersion maps ( c(H ) = 95 4 km s 1 and c(CO) = 136 20 km s 1 ). The stars lag behind the warm gas and represent a dynamically hotter system, as indicated by the observed V/ ratios (4.5 and 2.4 for the gas and the stars, respectively). Thanks to these IFS data we have disentangled the contribution of the stars and the interstellar medium to the NaD feature, finding that it is dominated by absorption of neutral gas clouds in the interstellar medium ( 2/3 of total EW). The 2D kinematics of the neutral gas shows a complex structure dominated by two main components. On the one hand, the thick slowly rotating disk ( V(NaD) = 81 12 km s 1 ) lags significantly compared to the ionized gas and the stars, and it has an irregular and o -center velocity dispersion map (with values of up to 150 km s 1 at 1 kpc from the nucleus). On the other hand, a kpc-scale neutral gas outflow perpendicular to the disk, as is revealed by the large blueshifted velocities (in the range 30 154 km s 1 ) observed along the galaxy’s semi-minor axis (within the inner 1.4 kpc). On the basis of a simple free wind scenario, we derive an outflowing mass rate ( ˙ Mw) in neutral gas of about 48 M yr 1 . Although this implies a global mass loading factor (i.e., = ˙ Mw/SFR) of 1.4, the 2D distribution of the ongoing SF as traced by the H emission map suggests a much larger value of associated with the inner regions (R < 200 pc), where the current observed star formation (SF) represents only 3 percent of the total. However, the relatively strong emission by supernovae in the central regions, as traced by the [FeII] emission, indicates recent strong episodes of SF. Therefore, our data show clear evidence of the presence of a strong outflow with large loading factors associated with the nuclear regions, where recent starburst activity took place about 7 Myr ago, although it currently shows relatively modest SF levels. All together these results strongly suggest that we are witnessing (nuclear) quenching due to SF feedback in IRAS F11506-3851. However, the relatively large mass of molecular gas detected in the nuclear region via the H2 1 0S(1) line suggests that further episodes of SF may take place again.
Bursting emission from PSR B0611+22

Over the past decade it has become apparent that a class of ‘bursting pulsars’ exist with the discovery of PSR J1752+2359 and PSR J1938+2213. In these pulsars, a sharp increase in the emission is observed that then tends to systematically drop-off from pulse-to-pulse. In this paper we describe the discovery of such a relationship in high-sensitivity observations of the young (characteristic age of 90,000 yrs) 0.33 s pulsar B0611+22 at both 327 MHz and 1400 MHz with the Arecibo radio telescope. While Nowakowski previously showed that B0611+22 has mode-switching properties, the data presented here show, for the first time, that this pulsar emits bursts with characteristic time-scales of several hundred seconds. At 327 MHz, the pulsar shows steady behaviour in one emission mode which is enhanced by bursting emission slightly offset in pulse phase from this steady emission. Contrastingly at 1400 MHz, the two modes appear to behave in a competing operation while still offset in phase. Using a fluctuation spectrum analysis, we also investigate each mode independently for subpulse drifting. Neither emission mode (i.e. during bursts or persistent emission) shows the presence of the drifting sub-pulse phenomenon. The bursting phenomena seen here appears to be a hybrid between bursting seen in other pulsars and the bistable profile illumination behaviour reported in two other pulsars by Rankin et al. Further examples of this cross-frequency behaviour are required, as this phenomenon may be quite common among the pulsar population.
The Many Faces of Edge Intelligence

Edge Intelligence (EI) is an emerging computing and communication paradigm that enables Artificial Intelligence (AI) functionality at the network edge. In this article, we highlight EI as an emerging and important field of research, discuss the state of research, analyze research gaps and highlight important research challenges with the objective of serving as a catalyst for research and innovation in this emerging area. We take a multidisciplinary view to reflect on the current research in AI, edge computing, and communication technologies, and we analyze how EI reflects on existing research in these fields. We also introduce representative examples of application areas that benefit from, or even demand the use of EI.
Efficacy and Safety of Pyrotinib in Human Epidermal Growth Factor Receptor 2-Positive Advanced Breast Cancer: A Multicenter, Retrospective, Real-World Study

Purpose Pyrotinib, a novel human epidermal growth factor receptor 2 (HER2)-targeted tyrosine kinase inhibitor (TKI), has led to remarkable survival outcomes in HER2-positive advanced breast cancer (ABC) in clinical trials and was approved for second-line standards of treatment for HER2+ ABC in China. However, the clinical trials could not fully reflect reality of clinical practice, and predictive factors were still lacking. This study aimed to assess the actual efficacy and safety of pyrotinib in HER2+ ABC in real-world setting. Patients and Methods In this multicenter, retrospective, observational real-world study, we analyzed 171 patients with HER2+ ABC, who received pyrotinib-based treatment from November 2017 to November 2020. The primary end point was progression-free survival (PFS). Secondary end points included overall survival (OS), objective response rate (ORR), clinical benefit rate (CBR) and safety. Results Up to November 30, 2021, the median PFS (mPFS) was 12.0 months for all patients. One hundred and sixty-two patients (94.7%) with measurable lesions had been included in efficacy assessment. The ORR and CBR were 45.1% and 81.5%, respectively. A significantly longer PFS was reported in patients who received pyrotinib as first-line treatment, had the ECOG-PS of 0–1, as well as those who were lapatinib-naive. In addition, multivariable analysis indicated that ECOG-PS of 2–4, positive hormone receptor (HR) status, and presence of visceral metastasis were independent negative predictors of PFS. As far as we know, this study first reported the survival outcome of pyrotinib cross-line treatment, with a mPFS of 5.0 months. All grades of adverse events (AEs) occurred in 171 patients (100%), and the most common AE was diarrhea (86.5%). Conclusion This study further demonstrated the outstanding efficacy and safety of pyrotinib and reported the potential predictors of survival in HER2+ ABC.
Combination of TyG Index and GRACE Risk Score as Long-Term Prognostic Marker in Patients with ACS Complicated with T2DM Undergoing PCI

Objective We aimed to investigate the prognostic value of the triglyceride-glucose (TyG) index combined the with Global Registry of Acute Coronary Events (GRACE) score in adult acute coronary syndrome (ACS) patients with type 2 diabetes mellitus (T2DM) who underwent percutaneous coronary intervention (PCI). Methods The study enrolled total 899 ACS patients with T2DM who underwent PCI. TyG index and the GRACE risk score were calculated and assessed by median. The correlation was analyzed by Spearman’s rank correlation coefficient. The cumulative major adverse cardiovascular event (MACE) curve was generated using the Kaplan–Meier method. Multivariate Cox regression was used to identify predictors of MACEs. Additionally, the receiver operating characteristic curve (ROC), net reclassification index (NRI) and Integrated Discrimination Improvement (IDI) were applied to analyze the performance of each single factor index and combined multivariate index in predicting MACE. Results In the ACS patients with T2DM after PCI, there were significant differences in the TyG index and GRACE risk score between the MACE group and the MACE-free group (P < 0.001). Kaplan–Meier analysis showed that the TyG index combined with the GRACE risk score was positively correlated with the occurrence of MACEs (log rank P < 0.001). Multivariate Cox regression analyses showed that the TyG index, the GRACE risk score, and the TyG index combined with the GRACE risk score were independent predictors of long-term MACEs (adjusted HR: 1.805; 95% CI: 1.479–2.203, P < 0.001; adjusted HR: 1.012; 95% CI: 1.009–1.016, P < 0.001; and adjusted HR: 2.337; 95% CI: 1.805–3.025, P < 0.001, respectively). Correlation analysis indicated that the TyG index was positively correlated with the GRACE risk score (R = 0.140, P < 0.001). The analysis of AUC, NRI and IDI revealed that the combined multivariate index performed better prognostic role than each single factor index in predicting the occurrence of MACE. Conclusion Both the GRACE risk score and the TyG index could be significant and independent predictors of clinical outcomes in ACS patients with T2DM after PCI. A combination of them could be enhanced predictions of clinical outcomes in these patients.
Markov Chain Monte Carlo

1 Mixing and Correlation Time Let’s suppose for simplicity that our Markov chain has only one eigenvector v with eigenvalue 1, so all the other eigenvalues are strictly< 1 in magnitude. As we saw last time, if we put the eigenvalues and their eigenvectors in decreasing order, 1= λ1 > |λ2| ≥ |λ3| ≥ . ≥ |λK | (1) then when we evolve some initial distribution p0 for many time steps, the second largest eigenvalue dominates:
Extraction and Analysis of Influencing Factors of Scientific and Technological Ability Improvement of University Teachers Based on Deep Learning Model

In order to improve the development and construction level of colleges and universities and help teachers improve their scientific and technological abilities, a model based on deep learning model for the extraction and analysis of factors affecting the improvement of college teachers’ scientific and technological abilities was proposed. This article analyzes the data of teaching evaluation and finds that the text contains students’ subjective understanding of teachers’ teaching quality defects. By extracting key words from students’ teaching evaluation texts and combining with the teaching evaluation indexes, a teaching evaluation label system integrating teaching evaluation texts is designed. In order to find the defects of teachers’ teaching ability, this article, based on the principle of data portrait, combines the characteristics of teachers’ personal basic information, curriculum information, teaching evaluation information, and social relations to portrait teachers. The experimental results show that the F1 value extracted from the evaluation labels fluctuates in the evaluation text data of different colleges, with the lowest value of 91.7% in the School of Statistics and the highest value of 95.8% in the School of Foreign Languages. The algorithm in this article has a higher F1 value of the evaluation label vector extracted from the evaluation text of different grades. F1 values showed a trend of gradient decline with the increase of grade, and the decreasing range became bigger and bigger. Conclusion. The constructed teacher portraits are more accurate and effective, and provide a comprehensive and effective data model for teaching ability improvement method recommendation strategy.
Anaplasma phagocytophilum in cattle parasitism in Benin: An emerging pathogen transmitted by ticks

Anaplasma phagocytophilum , a bacterium transmitted by ticks, is responsible for granulocytic anaplasmosis, an emerging zoonosis that has never been reported nor identified previously in Benin and in the West African sub-region. This study is designed not only to investigate the prevalence of the disease and evaluate mortalities recorded at Kpinnou farm after importing Girolando cattle from Brazil in 2014 but also to assess the prevalence of the emerging disease in Benin in the year 2014 period. A total number of 1427 ticks were collected, including 5 ml of blood from each one hundred cattle. Microscopic diagnosis reveals the presence of Rhipicephalus ( Boophilus ) spp. , Rhipicephalus microplus , Amblyomma variegatum , Rhipicephalus spp and Hyalomma spp. Blood analysis results reveal the occurrence of 55% positive cases for A. phagocytophilum . Considering the effeiciency of the methods, 100% of A. phagocytophilum reported as positive by microscopy appear to be also positive with molecular analysis. PCR has greater sensitivity and specificity even with microscopy showing appreciable specificity. This study concludes that Anaplasma phagocytophilum is the primary suspect responsible for the massive deaths observed in cattle in the study area.
Large-scale peculiar velocities through the galaxy luminosity function at z ~ 0.1

Abstract Peculiar motion introduces systematic variations in the observed luminosity distribution of galaxies. This allows one to constrain the cosmic peculiar velocity field from large galaxy redshift surveys. Using around half a million galaxies from the SDSS Data Release 7 at z ~ 0.1, we demonstrate the applicability of this approach to large datasets and obtain bounds on peculiar velocity moments and σ8, the amplitude of the linear matter power spectrum. Our results are in good agreement with the ΛCDM model and consistent with the previously reported ~ 1% zero-point tilt in the SDSS photometry. Finally, we discuss the prospects of constraining the growth rate of density perturbations by reconstructing the full linear velocity field from the observed galaxy clustering in redshift space.
Enhanced Distributed Consensus Filtering Over Lossy Wireless Sensor Networks With Application to Target Speed Tracking

This article presents a novel way of distributed consensus filtering with enhanced robustness over wireless sensor networks, where bounded-power disturbances related to modeling uncertainty and white Gaussian noises are included. Sensors are assumed to receive local observations and transmit them to their neighbors through lossy links. A distributed consensus filtering scheme, consisting of an optimal filter, a separated damping term, and a consensus tuning parameter, is considered through exchanging prior estimates among neighboring nodes, to achieve the cohesiveness among local estimates together with robust optimal estimation performance. A sufficient and necessary condition is conducted for determining the consensus parameter, leading to a nonconservative design way. Finally, to show the effectiveness of the presented results, an experiment of target speed tracking is included.
Monoidal Bousfield Localizations and Algebras over Operads

We give conditions on a monoidal model category M and on a set of maps C so that the Bousfield localization of M with respect to C preserves the structure of algebras over various operads. This problem was motivated by an example that demonstrates that, for the model category of equivariant spectra, preservation does not come for free, even for cofibrant operads. We discuss this example in detail and provide a general theorem regarding when localization preserves P-algebra structure for an arbitrary operad P. We characterize the localizations that respect monoidal structure and prove that all such localizations preserve algebras over cofibrant operads. As a special case we recover numerous classical theorems about preservation of algebraic structure under localization, in the context of spaces, spectra, chain complexes, and equivariant spectra. We also provide several new results in these settings, and we sharpen a recent result of Hill and Hopkins regarding preservation for equivariant spectra. To demonstrate our preservation result for non-cofibrant operads, we work out when localization preserves commutative monoids and the commutative monoid axiom, and again numerous examples are provided. Finally, we provide conditions so that localization preserves the monoid axiom.
A Virtual Sensing Concept for Nitrogen and Phosphorus Monitoring Using Machine Learning Techniques

Harmful cyanobacterial bloom (HCB) is problematic for drinking water treatment, and some of its strains can produce toxins that significantly affect human health. To better control eutrophication and HCB, catchment managers need to continuously keep track of nitrogen (N) and phosphorus (P) in the water bodies. However, the high-frequency monitoring of these water quality indicators is not economical. In these cases, machine learning techniques may serve as viable alternatives since they can learn directly from the available surrogate data. In the present work, a random forest, extremely randomized trees (ET), extreme gradient boosting, k-nearest neighbors, a light gradient boosting machine, and bagging regressor-based virtual sensors were used to predict N and P in two catchments with contrasting land uses. The effect of data scaling and missing value imputation were also assessed, while the Shapley additive explanations were used to rank feature importance. A specification book, sensitivity analysis, and best practices for developing virtual sensors are discussed. Results show that ET, MinMax scaler, and a multivariate imputer were the best predictive model, scaler, and imputer, respectively. The highest predictive performance, reported in terms of R2, was 97% in the rural catchment and 82% in an urban catchment.
Observer and observer-based H∞ control of generalized Hamiltonian systems

This paper deals with observer design for generalized Hamiltonian systems and its applications. First, by using the systems' structural properties, a new observer design method called Augment Plus Feedback is provided and two kinds of observers are obtained: non-adaptive and adaptive ones. Then, based on the obtained observer, H∞ control design is investigated for generalized Hamiltonian systems, and an observer-based control design is proposed. Finally, as an application to power systems, an observer and an observer-based H∞ control law are designed for single-machine infinite-bus systems.Simulations show that both the observer and controller obtained in this paper work very well.
RELATIVE ENTROPY OF ENTANGLEMENT FOR TWO-QUBIT STATE WITH z-DIRECTIONAL BLOCH VECTORS

So far there is no closed formula for relative entropy of entanglement of arbitrary two-qubit states. In this paper we present a method, which guarantees the derivation of the relative entropy of entanglement for most states that have z-directional Bloch vectors. It is shown that the closest separable states for those states also have z-directional Bloch vectors though there are few exceptions.
MOST discovers a multimode $\delta$ Scuti star in a triple system: HD 61199

Context. A field star, HD61199 (V approximate to 8), simultaneously observed with Procyon by the MOST (Microvariability & Oscillations of STars) satellite in continuous runs of 34, 17, and 34 days in 2004, 2005, and 2007, was found to pulsate in 11 frequencies in the delta Scuti range with amplitudes from 1.7 down to 0.09 mmag. The photometry also showed variations with a period of about four days. To investigate the nature of the longer period, 45 days of time-resolved spectroscopy was obtained at the Thuringer Landessternwarte Tautenburg in 2004. The radial velocity measurements indicate that HD61199 is a triple system. Aims. A delta Scuti pulsator with a rich eigenspectrum in a multiple system is promising for asteroseismology. Our objectives were to identify which of the stars in the system is the delta Scuti variable and to obtain the orbital elements of the system and the fundamental parameters of the individual components, which are constrained by the pulsation frequencies of the delta Scuti star.Methods. Classical Fourier techniques and least-squares multi-sinusoidal fits were applied to the MOST photometry to identify the pulsation frequencies. The groundbased spectroscopy was analysed with least-squares-deconvolution (LSD) techniques, and the orbital elements derived with the KOREL and ORBITX routines. Asteroseismic models were also generated. Results. The photometric and spectroscopic data are compatible with a triple system consisting of a close binary with an orbital period of 3.57 days and a d Scuti companion (HD61199 A) as the most luminous component. The d Scuti star is a rapid rotator with about v sin i = 130 km s(-1) and an upper mass limit of about 2.1 M-circle dot. For the close binary components, we find they are of nearly equal mass, with lower mass limits of about 0.7 M-circle dot. Comparisons to synthetic spectra indicate these stars have a late-F spectral type. The observed oscillation frequencies are compared to pulsation models to further constrain the evolutionary state and mass of HD61199 A. The orbit frequency of the close binary corresponds to the difference of the two d Scuti frequencies with the highest amplitudes a coincidence that is remarkable, but not explained.
Design of Intelligent Parking Management System Based on ARM and Wireless Sensor Network

Motor vehicles are changing the way people live, but they are also putting a huge strain on urban traffic. In the majority of major cities, parking has become the number one problem for car owners to get around. The management efficiency of car parks directly affects the traffic of the whole city. In order to improve the management efficiency of the car park, this paper designs an intelligent parking management system based on ARM and ZigBee wireless sensor network. Firstly, according to the internal environment and economic cost of the car park, ultrasonic sensors are used to monitor whether the parking space is empty or not. The information collected by the ultrasonic sensors is transmitted to the ARM host controller through the ZigBee wireless sensor network, and the ARM host controller determines whether there are free parking spaces based on the collected information. Secondly, Faster R-CNN, a deep learning algorithm, is selected as the license plate recognition model, and the Faster R-CNNN is improved by the residual module. Finally, in order to extend the lifetime of the ZigBee wireless network, the ZigBee routing algorithm is investigated, and an improved routing algorithm based on energy averaging is proposed. The effectiveness of the improved routing algorithm is demonstrated by a simulation analysis through NS2. The test results show that the designed intelligent parking management system is able to complete the functions of parking space detection and license plate recognition normally, thus effectively improving the efficiency of the car park and providing great convenience to motorists.