ABSTRACT
We present the Hubble imaging Probe of Extreme Environments and Clusters (HiPEEC) survey. We fit HST NUV to NIR broad-band and H α fluxes to derive star cluster ages, masses, and extinctions ...and determine the star formation rate (SFR) of six merging galaxies. These systems are excellent laboratories to trace cluster formation under extreme gas physical conditions, rare in the local Universe, but typical for star-forming galaxies at cosmic noon. We detect clusters with ages of 1–500 Myr and masses that exceed 107 M⊙. The recent cluster formation history and their distribution within the host galaxies suggest that systems such as NGC 34, NGC 1614, and NGC 4194 are close to their final coalescing phase, while NGC 3256, NGC 3690, and NGC 6052 are at an earlier/intermediate stage. A Bayesian analysis of the cluster mass function in the age interval 1–100 Myr provides strong evidence in four of the six galaxies that an exponentially truncated power law better describes the observed mass distributions. For two galaxies, the fits are inconclusive due to low number statistics. We determine power-law slopes β ∼ −1.5 to −2.0 and truncation masses, Mc, between 106 and a few times 107 M⊙, among the highest values reported in the literature. Advanced mergers have higher Mc than early/intermediate merger stage galaxies, suggesting rapid changes in the dense gas conditions during the merger. We compare the total stellar mass in clusters to the SFR of the galaxy, finding that these systems are among the most efficient environments to form star clusters in the local Universe.
Emotions are the most powerful information source to study the cognition, behaviour, and medical conditions of a person. Accurate identification of emotions helps in the development of affective ...computing, brain–computer interface, medical diagnosis system, etc. Electroencephalogram (EEG) signals are one such source to capture and study human emotions. In this Letter, a novel time-order representation based on the S-transform and convolutional neural network (CNN) is proposed for the identification of human emotions. EEG signals are transformed into time-order representation (TOR) based on the S-transform. This TOR is given as an input to CNN to automatically extract and classify the deep features. Emotional states of happiness, fear, sadness, and relax are classified with an accuracy of 94.58%. The superiority of the method is judged by evaluating four performance parameters and comparing it with existing state-of-the-art on the same dataset.
Abstract
Eridanus II (Eri II) is an ultrafaint dwarf (UFD) galaxy (
M
V
= −7.1) located at a distance close to the Milky Way virial radius. Early shallow color–magnitude diagrams (CMDs) indicated ...that it possibly hosted an intermediate-age or even young stellar population, which is unusual for a galaxy of this mass. In this paper, we present new Hubble Space Telescope/Advanced Camera for Surveys CMDs reaching the oldest main-sequence turnoff with excellent photometric precision and derive a precise star formation history (SFH) for this galaxy through CMD fitting. This SFH shows that the bulk of the stellar mass in Eri II formed in an extremely short star formation burst at the earliest possible time. The derived star formation rate profile has a width at half maximum of 500 Myr and reaches a value compatible with null star formation 13 Gyr ago. However, tests with mock stellar populations and with the CMD of the globular cluster M92 indicate that the star formation period could be shorter than 100 Myr. From the quantitative determination of the amount of mass turned into stars in this early star formation burst ( ∼2 × 10
5
M
⊙
) we infer the number of supernova (SN) events and the corresponding energy injected into the interstellar medium. For reasonable estimates of the Eri II virial mass and values of the coupling efficiency of the SN energy, we conclude that Eri II could be quenched by SN feedback alone, thus casting doubts on the need to invoke cosmic reionization as the preferred explanation for the early quenching of old UFD galaxies.
Automated electrocardiogram (ECG) beat classification is an important component of heart monitoring systems used for raising an emergency call during sudden cardiac disorder of patients. An automatic ...ECG beat classifier is proposed to exploit the bandwidth features that are exclusively extracted from analytic intrinsic mode functions (IMFs). The proposed methodology employs artificial bee colony (ABC) algorithm-based least-squares support vector machines (LSSVM) classifier to classify ECG beat types using radial basis function kernel. Simulation results illustrate that proposed classifier gives the best results with second IMF. This novelty lies in its unique combination of ABC with LSSVM classifier that efficiently exploits bandwidth features for automatic classification of ECG beats.
The unnatural activities of brain due to seizure events are analysed by electroencephalogram (EEG) signals which are captured from the brain. In this work, a methodology is proposed to classify the ...seizure EEG signals. In the proposed method, a novel sparse spectrum based empirical wavelet transform (SS-EWT) is applied to decompose the EEG signal into coefficients. From the obtained SS-EWT coefficients, the cross-information potential and normalised energy are extracted as features. Then these features are ranked using the RELIEFF method to obtain significant features. After ranking, these features are fed into the k-nearest neighbour (k-NN) classifier to classify EEG signals corresponding to different brain activities. In this work, the first classification problem is the classification of the seizure (S), seizure-free (F), and normal (Z) EEG signals in which obtained classification accuracy (Acc) is $96.67\%$96.67%. The second classification problem is the classification of S and Z EEG signals in which $100\%$100% Acc is achieved by the proposed method.
Sleep apnea (SA) event occurs due to restraint in normal respiration. It requires accurate diagnosis, because of neurotic and cardiac disorders. In this work, particle swarm optimisation (PSO)-based ...Hermite decomposition algorithm is proposed, for identification of SA event using electroencephalogram (EEG) signals with parameterised classifier. The information from randomly varying complex EEG signals is extracted in terms of PSO optimised Hermite functions (HFs), with constraint of minimum error function. The Hermite coefficients computed from HFs-based statistical features are applied as input to PSO parameterised least square support vector machine classifier. The proposed decomposition for EEG signals provides negligible mean value of error function and obtain best results for identification of apnea event compared to existing methods.
Purpose
Atypical teratoid/rhabdoid tumors (ATRT) of the central nervous system (CNS) are rare tumors with a poor prognosis and variable use of either focal or craniospinal (CSI) radiotherapy (RT). ...Outcomes on the prospective Pediatric Proton/Photon Consortium Registry (PPCR) were evaluated according to RT delivered.
Methods
Pediatric patients receiving RT were prospectively enrolled on PPCR to collect initial patient, disease, and treatment factors as well as provide follow-up for patient outcomes. All ATRT patients with evaluable data were included. Kaplan–Meier analyses with log-rank p-values and cox proportional hazards regression were performed.
Results
The PPCR ATRT cohort includes 68 evaluable ATRT patients (median age 2.6 years, range 0.71–15.40) from 2012 to 2021. Median follow-up was 40.8 months (range 3.4–107.7). Treatment included surgery (65% initial gross total resection or GTR), chemotherapy (60% with myeloablative therapy including stem cell rescue) and RT. For patients with M0 stage (n = 60), 50 (83%) had focal RT and 10 (17%) had CSI. Among patients with M + stage (n = 8), 3 had focal RT and 5 had CSI. Four-year overall survival (OS, n = 68) was 56% with no differences observed between M0 and M + stage patients (p = 0.848). Local Control (LC) at 4 years did not show a difference for lower primary dose (50–53.9 Gy) compared to ≥ 54 Gy (73.3% vs 74.7%, p = 0.83). For patients with M0 disease, four-year OS for focal RT was 54.6% and for CSI was 60% (Hazard Ratio 1.04, p = 0.95. Four-year event free survival (EFS) among M0 patients for focal RT was 45.6% and for CSI was 60% (Hazard Ratio 0.71, p = 0.519). For all patients, the 4-year OS comparing focal RT with CSI was 54.4% vs 60% respectively (p = 0.944), and the 4-year EFS for focal RT or CSI was 42.8% vs 51.4% respectively (p = 0.610).
Conclusion
The PPCR ATRT cohort found no differences in outcomes according to receipt of either higher primary dose or larger RT field (CSI). However, most patients were M0 and received focal RT. A lower primary dose (50.4 Gy), regardless of patient age, is appealing for further study as part of multi-modality therapy.
.
Dynamic nuclear polarization (DNP) results in a substantial nuclear polarization enhancement through a transfer of the magnetization from electrons to nuclei. Recent years have seen considerable ...progress in the development of DNP experiments directed towards enhancing sensitivity in biological nuclear magnetic resonance (NMR). This review covers the applications, hardware, polarizing agents, and theoretical descriptions that were developed at the Francis Bitter Magnet Laboratory at Massachusetts Institute of Technology for high-field DNP experiments. In frozen dielectrics, the enhanced nuclear polarization developed in the vicinity of the polarizing agent can be efficiently dispersed to the bulk of the sample via
1
H spin diffusion. This strategy has been proven effective in polarizing biologically interesting systems, such as nanocrystalline peptides and membrane proteins, without leading to paramagnetic broadening of the NMR signals. Gyrotrons have been used as a source of high-power (5–10 W) microwaves up to 460 GHz as required for the DNP experiments. Other hardware has also been developed allowing in situ microwave irradiation integrated with cryogenic magic-angle-spinning solid-state NMR. Advances in the quantum mechanical treatment are successful in describing the mechanism by which new biradical polarizing agents yield larger enhancements at higher magnetic fields. Finally, pulsed methods and solution experiments should play a prominent role in the future of DNP.
Dust grains are nucleation centers and catalysts for the growth of icy mantles in quiescent interstellar clouds, the products of which may accumulate into preplanetary matter when new stars and solar ...systems form within the clouds. In this paper, we present the first spectroscopic detections of silicate dust and the molecular ices H sub(2)O, CO, and CO sub(2) in the vicinity of the prestellar core L183 (L134N). An infrared photometric survey of the cloud was used to identify reddened background stars, and we present spectra covering solid-state absorption features in the wavelength range 2-20 mu m for nine of them. The mean composition of the ices in the best-studied line of sight (toward J15542044-0254073) is H sub(2)O:CO:CO sub(2) approx = 100:40:24. The ices are amorphous in structure, indicating that they have been maintained at low temperature (<, ~ 15 K) since formation. The ice column density N(H sub(2)O) correlates with reddening by dust, exhibiting a threshold effect that corresponds to the transition from unmantled grains in the outer layers of the cloud to ice-mantled grains within, analogous to that observed in other dark clouds. A comparison of results for L183 and the Taurus and IC 5146 dark clouds suggests common behavior, with mantles first appearing in each case at a dust column corresponding to a peak optical depth tau sub(9.7) = 0.15 + or - 0.03 in the silicate feature. Our results support a previous conclusion that the color excess EJ - K does not obey a simple linear correlation with the total dust column in lines of sight that intercept dense clouds. The most likely explanation is a systematic change in the optical properties of the dust as the density increases.
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