Low Surface Brightness Galaxies Selected by Different Model Fitting

We present a study of low surface brightness galaxies(LSBGs) selected by fitting the images for all the galaxies inα.40 SDSS DR7 sample with two kinds of single-component models and two kinds of two-component models(disk+bulge):single exponential,single sersic,exponential+deVaucular(exp+deV),and exponential+sérsic(exp+ser).Under the criteria of the B band disk central surface brightness μ_(0,disk)(B)≥22.5 mag arcsec^(-2) and the axis ratio b/a> 0.3,we selected four none-edge-on LSBG samples from each of the models which contain 1105,1038,207,and 75 galaxies,respectively.There are 756 galaxies in common between LSBGs selected by exponential and sersic models,corresponding to 68.42% of LSBGs selected by the exponential model and 72.83% of LSBGs selected by the sersic model,the rest of the discrepancy is due to the difference in obtaining μ_(0) between the exponential and sersic models.Based on the fitting,in the range of 0.5≤n≤1.5,the relation of μ_(0) from two models can be written as μ_(0,sérsic)-μ_(0,exp)=-1.34(n-1).The LSBGs selected by disk+bulge models(LSBG_(2)comps) are more massive than LSBGs selected by single-component models(LSBG_1comp),and also show a larger disk component.Though the bulges in the majority of our LSBG_(2)comps are not prominent,more than 60% of our LSBG_(2)comps will not be selected if we adopt a single-component model only.We also identified 31 giant low surface brightness galaxies(gLSBGs) from LSBG_(2)comps.They are located at the same region in the color-magnitude diagram as other gLSBGs.After we compared different criteria of gLSBGs selection,we find that for gas-rich LSBGs,M_(*)> 10^(10)M_⊙ is the best to distinguish between gLSBGs and normal LSBGs with bulge.

Four Late-type Galaxies with Double Radio Lobes and Properties of Such Galaxies

The triggering mechanism for radio lobes from late-type galaxies is not fully understood.More samples are desired for a thorough investigation and statistics.By utilizing the optical data from the newly released Dark Energy Spectroscopic Instrument imaging surveys and the radio sources from the NRAO VLA Sky Survey and the Faint Images of the Radio Sky at Twenty-centimeter,we identify four Late-type Galaxies with double Radio Lobes(La GRLs):J0217-3645,J0947+6220,J1412+3723 and J1736+5108.Including previously known La GRLs,we confirm the correlation between radio power P_(1.4GHz)and stellar mass M_(*)of host galaxies.Most(25/35)La GRLs belong to the blue cloud galaxies,while the newly identified cases in this work are located within the region of the red sequence.We find a clear correlation between the differential radio power,i.e.,the offset from the P_(1.4GHz)-M_(*)relation,and the galaxy color,indicating that bluer galaxies at a fixed M_(*)tend to host more powerful radio lobes.Furthermore,the majority(31/36)of La GRLs are either located in a galaxy group or displaying a disturbed morphology.We suggest that all of the galaxy mass,color and surrounding environment could play important roles in triggering radio lobes in late-type galaxies.

Stellar Populations of AGN-host Dwarf Galaxies Selected with Different Methods

In this paper we investigate the stellar populations and star formation histories of 235 active galactic nucleus(AGN)-host dwarf galaxies,consisting of four samples identified separately with different methods(i.e.,radio,X-ray,mid-IR and variability),utilizing the synthesis code STARLIGHT and spectra from the Sloan Digital Sky Survey Data Release 8.Our results show that the variability sample is the oldest,while the mid-IR sample is the youngest,for which the luminosity at 4020?is dominated(>50%)by the young population(t<10~8yr).The light-weighted mean stellar age of the whole sample is in general about 0.7 dex younger than the optical sample studied in Cai et al.We compare the population results between fitting models with and without a power-law(PL)component and find that the neglect of a PL component would lead to an under-and over-estimation by 0.2 and0.1 dex for the light-and mass-weighted mean stellar age,respectively,for our sample of dwarf galaxies,which has a mean fractional contribution of~16%from the AGN.In addition,we obtain further evidence for a possible suppression of star formation in the host galaxy by the central AGN.We also find that there exists an anticorrelation between the extinction-corrected[O III]luminosity and light-weighted mean stellar age,confirming our previous finding that there is a physical connection between AGN and star-forming activities in AGN-host dwarfs.

Morphological Classification of Infrared Galaxies Based on WISE

This study introduces a novel convolutional neural network,the WISE Galaxy Classification Network(WGC),for classifying spiral and elliptical galaxies using Wide-field Infrared Survey Explorer(WISE)images.WGC attains an accuracy of 89.03%,surpassing the combined use of K-means or SVM with the Color-Color method in more accurately identifying galaxy morphologies.The enhanced variant,WGC_mag,integrates magnitude parameters with image features,further boosting the accuracy to 89.89%.The research also delves into the criteria for galaxy classification,discovering that WGC primarily categorizes dust-rich images as elliptical galaxies,corresponding to their lower star formation rates,and classifies less dusty images as spiral galaxies.The paper explores the consistency and complementarity of WISE infrared images with SDSS optical images in galaxy morphology classification.The SDSS Galaxy Classification Network(SGC),trained on SDSS images,achieved an accuracy of 94.64%.The accuracy reached 99.30% when predictions from SGC and WGC were consistent.Leveraging the complementarity of features in WISE and SDSS images,a novel variant of a classifier,namely the Multi-band Galaxy Morphology Integrated Classifier,has been developed.This classifier elevates the overall prediction accuracy to 95.39%.Lastly,the versatility of WGC was validated in other data sets.On the HyperLEDA data set,the distinction between elliptical galaxies and Sc,Scd and Sd spiral galaxies was most pronounced,achieving an accuracy of 90%,surpassing the classification results of the Galaxy Zoo 2 labeled WISE data set.This research not only demonstrates the effectiveness of WISE images in galaxy morphology classification but also represents an attempt to integrate multi-band astronomical data to enhance understanding of galaxy structures and evolution.

The Clumpy Structure of Five Star-bursting Dwarf Galaxies in the MaNGA Survey

The star-forming clumps in star-bursting dwarf galaxies provide valuable insights into understanding the evolution of dwarf galaxies.In this paper,we focus on five star-bursting dwarf galaxies featuring off-centered clumps in the Mapping Nearby Galaxies at Apache Point Observatory survey.Using the stellar population synthesis software Fitting Analysis using Differential evolution Optimization,we obtain the spatially resolved distribution of the star formation history,which allows us to construct the g-band images of the five galaxies at different ages.These images can help us to probe the evolution of the morphological structures of these galaxies.While images of a stellar population older than 1 Gyr are typically smooth,images of a stellar population younger than 1 Gyr reveal significant clumps,including multiple clumps which appear at different locations and even different ages.To study the evolutionary connections of these five galaxies to other dwarf galaxies before their star-forming clumps appear,we construct the images of the stellar populations older than three age nodes,and define them to be the images of the"host"galaxies.We find that the properties such as the central surface brightness and the effective radii of the hosts of the five galaxies are in between those of dwarf ellipticals(dEs)and dwarf irregulars(dIrrs),with two clearly more similar to dEs and one more similar to dIrrs.Among the five galaxies,8257-3704 is particularly interesting,as it shows a previous starburst event that is not quite visible from its gri image,but only visible from images of the stellar population at a few hundred million years.The star-forming clump associated with this event may have appeared at around 600 Myr ago and disappeared at around 40 Myr ago.

Cosmological Constraints on Neutrino Masses in Light of JWST Red and Massive Candidate Galaxies

The overabundance of the red and massive candidate galaxies observed by the James Webb Space Telescope(JWST)implies efficient structure formation or large star formation efficiency at high redshift z~10.In the scenario of a low or moderate star formation efficiency,because massive neutrinos tend to suppress the growth of structure of the universe,the JWST observation tightens the upper bound of the neutrino masses.Assuming A cold dark matter cosmology and a star formation efficiency∈[0.05,0.3](flat prior),we perform joint analyses of Planck+JWST and Planck+BAO+JWST,and obtain improved constraints∑m_(ν)<0.196 eV and ∑m_(ν)+<0.111 eV at 95% confidence level,respectively.Based on the above assumptions,the inverted mass ordering,which implies ∑m_(ν)≥0.1 eV,is excluded by Planck+BAO+JWST at 92.7% confidence level.

Comparing the Structural Parameters of the Milky Way to Other Spiral Galaxies

The structural parameters of a galaxy can be used to gain insight into its formation and evolution history.In this paper,we strive to compare the Milky Way’s structural parameters to other,primarily edge-on,spiral galaxies in order to determine how our Galaxy measures up to the Local Universe.For our comparison,we use the galaxy structural parameters gathered from a variety of literature sources in the optical and near-infrared wave bands.We compare the scale length,scale height,and disk flatness for both the thin and thick disks,the thick-to-thin disk mass ratio,the bulge-to-total luminosity ratio,and the mean pitch angle of the Milky Way’s spiral arms to those in other galaxies.We conclude that many of the Milky Way’s structural parameters are largely ordinary and typical of spiral galaxies in the Local Universe,though the Galaxy’s thick disk appears to be appreciably thinner and less extended than expected from zoom-in cosmological simulations of Milky Way-mass galaxies with a significant contribution of galaxy mergers involving satellite galaxies.

The Mass Assembly History for Galaxies with MaNGA

How galaxies assemble masses through their own star formation or interaction with the external environment is still an important topic in the field of galaxy formation and evolution.We use Value Added Catalogs with galaxy features that are spatially and temporally resolved from Sloan Digital Sky Survey Data Release 17 to investigate the mass growth histories of early-type galaxies(ETGs)and late-type galaxies(LTGs).We find that the mass growth of ETGs is earlier than that of LTGs for massive galaxies(M_(*)>10^(10)M_⊙),while low-mass(M_(*)≤10^(10)M_⊙)ETGs have statistically similar mass assembly histories as low-mass LTGs.The stellar metallicity of all massive galaxies shows a negative gradient and basically does not change with time.However,in low-mass galaxies,the stellar metallicity gradient of elliptical galaxies is negative,and the stellar metallicity gradient of lenticular and spiral galaxies evolves from positive to negative.ETGs are not all in a high-density environment,but exhibit mass dependence.As the tidal strength increases,the star formation rate of low-mass ETGs rapidly decreases.These results support a picture where massive galaxies exhibit inside-out quenching mode,while low-mass galaxies show outside-in quenching mode.Environmental effects play an important role in regulating the mass assembly histories of low-mass ETGs.

Lottery Numbers and Ordered Statistics

The lottery has long captivated the imagination of players worldwide, offering the tantalizing possibility of life-changing wins. While winning the lottery is largely a matter of chance, as lottery drawings are typically random and unpredictable. Some people use the lottery terminal randomly generates numbers for them, some players choose numbers that hold personal significance to them, such as birthdays, anniversaries, or other important dates, some enthusiasts have turned to statistical analysis as a means to analyze past winning numbers identify patterns or frequencies. In this paper, we use order statistics to estimate the probability of specific order of numbers or number combinations being drawn in future drawings.

Quantifying the Tension between Cosmological Models and JWST Red Candidate Massive Galaxies

We develop a Python tool to estimate the tail distribution of the number of dark matter halos beyond a mass threshold and in a given volume in a light-cone.The code is based on the extended Press-Schechter model and is computationally efficient,typically taking a few seconds on a personal laptop for a given set of cosmological parameters.The high efficiency of the code allows a quick estimation of the tension between cosmological models and the red candidate massive galaxies released by the James Webb Space Telescope,as well as scanning the theory space with the Markov Chain Monte Carlo method.As an example application,we use the tool to study the cosmological implication of the candidate galaxies presented in Labbéet al.The standard Λcold dark matter(ΛCDM)model is well consistent with the data if the star formation efficiency can reach~0.3 at high redshift.For a low star formation efficiency ε~0.1,theΛCDM model is disfavored at~2σ-3σconfidence level.

A Machine Learning Made Catalog of FR-Ⅱ Radio Galaxies from the FIRST Survey

We present an independent catalog(FRIIRGcat)of 45,241 Fanaroff–Riley TypeⅡ(FR-Ⅱ)radio galaxies compiled from the Very Large Array Faint Images of the Radio Sky at Twenty-centimeters(FIRST)survey and employed the deep learning method.Among them,optical and/or infrared counterparts are identified for 41,425 FR-Ⅱs.This catalog spans luminosities 2.63×10^(22)≤L_(rad)≤6.76×10^(29)W Hz^(-1)and redshifts up to z=5.01.The spectroscopic classification indicates that there are 1431 low-excitation radio galaxies and 260 high-excitation radio galaxies.Among the spectroscopically identified sources,black hole masses are estimated for 4837 FR-Is,which are in 10^(7.5)■M_(BH)■10^(9.5)M_(⊙).Interestingly,this catalog reveals a couple of giant radio galaxies(GRGs),which are already in the existing GRG catalog,confirming the efficiency of this FR-I catalog.Furthermore,284new GRGs are unveiled in this new FR-I sample;they have the largest projected sizes ranging from 701 to1209 kpc and are located at redshifts 0.31<z<2.42.Finally,we explore the distribution of the jet position angle and it shows that the faint Images of the FIRST images are significantly affected by the systematic effect(the observing beams).The method presented in this work is expected to be applicable to the radio sky surveys that are currently being conducted because they have finely refined telescope arrays.On the other hand,we are expecting that further new methods will be dedicated to solving this problem.

Close Major-merger Pairs at z=0: Star-forming Galaxies with Pseudobulges

We present a study of star-forming galaxies (SFGs) with pseudobulges (bulges with Sérsic index n<2) in a loca close major-merger galaxy pair sample (H-KPAIR).With data from new aperture photometries in the optical and near-infrared bands (aperture size of 7 kpc) and from the literature,we find that the mean Age of central stellar populations in Spirals with pseudobulges is consistent with that of disky galaxies and is nearly constant against the bulge-to-total ratio (B/T).Paired Spirals have a slightly lower fraction of pure disk galaxies (B/T≤0.1) than their counterparts in the control sample.Compared to SFGs with classical bulges,those with pseudobulges have a higher (>2σ) mean of specific star formation rate (sSFR) enhancement (sSFR_(enh)=0.33±0.07 versus sSFR_(enh)=0.12±0.06) and broader scatter (by~1 dex).The eight SFGs that have the highest sSFR_(enh)in the sample all have pseudobulges.A majority (69%) of paired SFGs with strong enhancement (having sSFR more than5 times the median of the control galaxies) have pseudobulges.The Spitzer data show that the pseudobulges in these galaxies are tightly linked to nuclear/circum-nuclear starbursts.Pseudobulge SFGs in S+S and in S+E pairs have significantly (>3σ) different sSFR enhancement,with the means of sSFR_(enh)=0.45±0.08 and-0.04±0.11respectively.We find a decrease in the sSFR enhancements with the density of the environment for SFGs with pseudobulges.Since a high fraction (5/11) of pseudobulge SFGs in S+E pairs are in rich groups/clusters (loca density N_(1Mpc)≥7),the dense environment might be the cause for their low s SFR_(enh).

Classical Cosmology I. Anomalous Redshift for Galaxies in NED-D

Three mechanisms for an alternative to the Doppler effect as an explanation for the redshift are reviewed. A fourth mechanism is the attenuation of the light as given by the Beer-Lambert law. The average value of the Hubble constant is therefore derived by processing the galaxies of the NED-D catalog in which the distances are independent of the redshift. The observed anisotropy of the Hubble constant is reproduced by adopting a rim model, a chord model, and both 2D and 3D Voronoi diagrams.

Dark Galaxies, Sun-Earth-Moon Interaction, Tunguska Event—Explained by WUM

Great experimental results and observations achieved by Astronomy in the last decades revealed new unexplainable phenomena. Astronomers have conclusive new evidence that a recently discovered “dark galaxy” is, in fact, an object the size of a galaxy, made entirely of dark matter. They found that the speed of the Earth’s rotation varies randomly each day. 115 years ago, the Tunguska Event was observed, and astronomers still do not have an explanation of It. Main results of the present article are: 1) Dark galaxies explained by the spinning of their Dark Matter Cores with the surface speed at equator less than the escape velocity. Their Rotational Fission is not happening. Extrasolar systems do not emerge;2) 21-cm Emission explained by the self-annihilation of Dark Matter particles XIONs (5.3 μeV);3) Sun-Earth-Moon Interaction explained by the influence of the Sun’s and the Moon’s magnetic field on the electrical currents of the charged Geomagma (the 660-km layer), and, as a result, the Earth’s daylength varies;4) Tunguska Event explained by a huge atmospheric explosion of the Superbolide, which was a stable Dark Matter Bubble before entering the Earth’s atmosphere.

Evaluation of Serum Anti-Müllerian Hormone (AMH) Values for 28,016 Bulgarian Women: Prognostic Statistical Model of Age Specific AMH Declining

The present study aims to establish a relationship between serum AMH levels and age in a large group of women living in Bulgaria, as well as to establish reference age-specific AMH levels in women that would serve as an initial estimate of ovarian age. A total of 28,016 women on the territory of the Republic of Bulgaria were tested for serum AMH levels with a median age of 37.0 years (interquartile range 32.0 to 41.0). For women aged 20 - 29 years, the Bulgarian population has relatively high median levels of AMH, similar to women of Asian origin. For women aged 30 - 34 years, our results are comparable to those of women living in Western Europe. For women aged 35 - 39 years, our results are comparable to those of women living in the territory of India and Kenya. For women aged 40 - 44 years, our results were lower than those for women from the Western European and Chinese populations, close to the Indian and higher than Korean and Kenya populations, respectively. Our results for women of Bulgarian origin are also comparable to US Latina women at age 30, 35 and 40 ages. On the base on constructed a statistical model to predicting the decline in AMH levels at different ages, we found non-linear structure of AMH decline for the low AMH 3.5) the dependence of the decline of AMH on age was confirmed as linear. In conclusion, we evaluated the serum level of AMH in Bulgarian women and established age-specific AMH percentile reference values based on a large representative sample. We have developed a prognostic statistical model that can facilitate the application of AMH in clinical practice and the prediction of reproductive capacity and population health.

Rapid Prediction of Wastewater Index Using CNN Architecture and PLS Series Statistical Methods

Chemical oxygen demand (COD) is an important index to measure the degree of water pollution. In this paper, near-infrared technology is used to obtain 148 wastewater spectra to predict the COD value in wastewater. First, the partial least squares regression (PLS) model was used as the basic model. Monte Carlo cross-validation (MCCV) was used to select 25 samples out of 148 samples that did not conform to conventional statistics. Then, the interval partial least squares (iPLS) regression modeling was carried out on 123 samples, and the spectral bands were divided into 40 subintervals. The optimal subintervals are 20 and 26, and the optimal correlation coefficient of the test set (RT) is 0.58. Further, the waveband is divided into five intervals: 17, 19, 20, 22 and 26. When the number of joint intervals under each interval is three, the optimal RT is 0.71. When the number of joint subintervals is four, the optimal RT is 0.79. Finally, convolutional neural network (CNN) was used for quantitative prediction, and RT was 0.9. The results show that CNN can automatically screen the features inside the data, and the quantitative prediction effect is better than that of iPLS and synergy interval partial least squares model (SiPLS) with joint subinterval three and four, indicating that CNN can be used for quantitative analysis of water pollution degree.

Effect Evaluation of CBL Combined with Rain Classroom Teaching Method in Medical Statistics

Objective: To explore the application effect of CBL combined with rain classroom teaching method in medical statistics courses. Methods: The undergraduate students of medical imaging technology in 2019 and 2020 in a university were selected as the research objects. A cluster sampling method was used to select 79 undergraduate students from 2019 in the control group and 75 undergraduate students from 2020 in the experimental group. Traditional teaching method and CBL combined with rain classroom teaching method was used in the control group and experimental group respectively. The final examination scores of the two groups were compared. In experimental group, the correlation between the average score in the rain classroom and the final examination score was tested, and the teaching effect was evaluated. Results: The average score of final examination in experimental group and control group was 79.13 ± 10.32 points and 71.54 ± 14.752 points, respectively, which had a statistically significant difference (Z = 2.586, P = 0.012);the final examination scores of the students in the experimental group were positively correlated with the average scores of the rain classroom (r = 0.372, P = 0.001), and the proportion of satisfaction in the experimental group was 94.7%. Conclusion: The CBL combined with rain classroom teaching method can improve the teaching effectiveness of medical statistics courses.

Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

In this present time,Human Activity Recognition(HAR)has been of considerable aid in the case of health monitoring and recovery.The exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and significance.Although many research works conducted on Smart Healthcare Monitoring,there remain a certain number of pitfalls such as time,overhead,and falsification involved during analysis.Therefore,this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning(SPR-SVIAL)for Smart Healthcare Monitoring.At first,the Statistical Partial Regression Feature Extraction model is used for data preprocessing along with the dimensionality-reduced features extraction process.Here,the input dataset the continuous beat-to-beat heart data,triaxial accelerometer data,and psychological characteristics were acquired from IoT wearable devices.To attain highly accurate Smart Healthcare Monitoring with less time,Partial Least Square helps extract the dimensionality-reduced features.After that,with these resulting features,SVIAL is proposed for Smart Healthcare Monitoring with the help of Machine Learning and Intelligent Agents to minimize both analysis falsification and overhead.Experimental evaluation is carried out for factors such as time,overhead,and false positive rate accuracy concerning several instances.The quantitatively analyzed results indicate the better performance of our proposed SPR-SVIAL method when compared with two state-of-the-art methods.

Comparative Analysis of Statistical Thickness Models for the Determination of the External Specific Surface and the Surface of the Micropores of Materials: The Case of a Clay Concrete Stabilized Using Sugar Cane Molasses

In this work, four empirical models of statistical thickness, namely the models of Harkins and Jura, Hasley, Carbon Black and Jaroniec, were compared in order to determine the textural properties (external surface and surface of micropores) of a clay concrete without molasses and clay concretes stabilized with 8%, 12% and 16% molasses. The results obtained show that Hasley’s model can be used to obtain the external surfaces. However, it does not allow the surface of the micropores to be obtained, and is not suitable for the case of simple clay concrete (without molasses) and for clay concretes stabilized with molasses. The Carbon Black, Jaroniec and Harkins and Jura models can be used for clay concrete and stabilized clay concrete. However, the Carbon Black model is the most relevant for clay concrete and the Harkins and Jura model is for molasses-stabilized clay concrete. These last two models augur well for future research.

The “Dead Universe” Theory: Natural Separation of Galaxies Driven by the Remnants of a Supermassive Dead Universe

This article explores the dead universe theory as a novel interpretation for the origin and evolution of the universe, suggesting that our cosmos may have originated from the remnants of a preceding universe. This perspective challenges the conventional Big Bang theory, particularly concerning dark matter, the expansion of the universe, and the interpretation of phenomena such as gravitational waves.