Cluster Members Research Articles

CO outflows from young stars in the NGC2023 cluster

Young early-type HAeBe stars are still embedded in the molecular clouds in which they formed. They illuminate reflection nebulae, which shape the surrounding molecular cloud and may trigger star formation. They are therefore ideal places to search for ongoing star formation activity. NGC\,2023 is illuminated by the Herbig Be star HD\,37903. It is the most massive member of a small young cluster with about 30 PMS stars, several of which are Class I objects that still heavily accrete. It might therefore be expected that they might drive molecular outflows. We examined the whole region for outflows. We analyzed previously published APEX data to search for and characterize the outflows in the NGC\,2023 region. This is the first systematic search for molecular outflows in this region. Since the outflows were mapped in several CO transitions, we can determine their properties quite well. We have discovered four molecular outflows in the vicinity of NGC\,2023, three of which are associated with Class I objects. MIR-63, a bright mid-infrared and submillimeter Class I source, is a binary with a separation of 2 and drives two bipolar outflows orthogonal to each other. The large southeast--northwest outflow excites the Herbig-Haro flow HH\,247. MIR-73, a Class I object, which is also a far-infrared source, drives a pole-on outflow. MIR-62 is a Class II object with strong infrared excess and a luminosity of 7 It is not detected in the far-infrared. The Class I sources have bolometric luminosities of about 20 or lower, that is, they are all low-mass stars. One other far-infrared source, MIR-75, may have powered an outflow in the past because it now illuminates an egg-shaped cavity. The four outflows are all powered by young stars and are located in the immediate vicinity of NGC\,2023. They are at a similar evolutionary stage, which suggests that their formation may have been triggered by the expanding region.

Multi-hop clustering routing protocol design based on simultaneous wireless information and power transfer technology and imperfect spectrum sensing for EH-CRSNs

Existing clustering routing protocols for multi-hop energy harvesting-cognitive radio sensor networks (EH-CRSNs) generally assume perfect spectrum sensing, which is not aligned with the practical spectrum sensing capabilities of nodes in real networks. Additionally, the severe imbalance in residual energy among cluster heads (CHs) negatively affects the successful data delivery. To resolve these problems, this paper introduces a simultaneous wireless information and power transfer (SWIPT)- and imperfect spectrum sensing-based multi-hop clustering routing protocol (ES-ISSMCRP). ES-ISSMCRP makes full use of downlink EH and intra-cluster SWIPT technologies to replenish and equalize the remaining energy among nodes, further extending network lifespan while maintaining network surveillance capabilities. Specifically, to reduce the adverse impact of imperfect spectrum sensing on network performance and improve energy utilization, this paper proposes an EH-based energy level function and associated selection criteria for CHs and relays, facilitating distributed cluster formation and multi-hop routing selection between clusters. To equalize the residual energy among nodes within a cluster, ES-ISSMCRP protocol enables cluster members (CMs) to decide whether employ SWIPT technology with a power splitting (PS) receiver architecture to transmit energy to their CH while sending data. The actual energy value transmitted by CMs using SWIPT technology is deduced by calculating the PS ratio and the expected energy expenditure of nodes for data transmission. Simulation results show that ES-ISSMCRP protocol offers significant improvements over other comparative protocols in terms of extending network lifespan and enhancing network surveillance capabilities.

The galaxy cluster AC114. III. The role of galaxy clusters in the mass-metallicity relation

The mass-metallicity relation (MZR) is a powerful tool to constrain internal physical processes that drive the chemical evolution of galaxies. However, the construction of this relation is carried out with field star-forming galaxies in big data surveys where environmental effects are either negligible or not studied in detail. We study the role of galaxy clusters in the MZR and its evolution at z=0.317 with star-forming members of AC114 (ABELL S1077). The purpose of this work is to understand how both the environmental effects and dynamical events modify the chemical evolution in this galaxy cluster. Spectroscopic VIMOS/VLT data was used to select cluster members and classify the galaxy sample in star-forming and passive galaxies. Gas-phase metallicities were estimated by using the strong-line method O3N2 calibrated on Te-based oxygen abundances. Available optical and near-infrared (NIR) photometry from DECaLS DR10 and the VIKING DR4 ESO survey was used to derive the stellar mass of the galaxy sample. AC114 is dominated by passive galaxies located in the central region of the cluster, whereas the star-forming members tend to be located outside this region. The constructed MZR from the latter indicates that star-forming galaxies have a lower metal content than foreground galaxies (spanning redshifts up to z=0.28), and the same or even lower metallicities with respect to background galaxies (spanning redshifts 0.34 to 0.70). Additionally, it shows a higher scatter of $ = 0.17$ dex, consistent with MZRs of galaxy clusters reported in the literature. The MZR at z=0.317 is downshifted by 0.19 dex on average with respect to local galaxies. Comparing the AC114-MZR with the field MZR at the same redshift, two galaxies are found to be more metal-rich than the field ones by $ 0.10$ dex. Likely as a result of ram-pressure stripping, star-forming galaxies deviate more from the MZR than field galaxies at the same redshift. Star-forming galaxies in the cluster are in general metal-poorer than field galaxies at the same redshfit up to $ 0.22$ dex, and show a MZR that is slightly shallower in slope compared with that of field galaxies. With a redshift analysis, three substructures were identified: star-forming galaxies in the main component show a higher scatter of 0.20 dex in metallicity than both the front and back ones, with a scatter of 0.07 and 0.11 dex, respectively. Star-forming galaxies located outside the central region of AC114 are driving the shallower slope of the cluster MZR. The slightly shallower slope and high scatter of AC114 with respect to foreground and background galaxies in the mass-metallicity plane indicates that galaxies are suffering from environmental and dynamical effects. Ram-pressure stripping and strangulation are likely the main drivers in increasing the metallicities of at least two star-forming members with respect to the field MZR at the same redshift. However, the lower metallicities of the star-forming black members, which drive the flatter slope of the AC114-MZR, can be explained by strong metal-poor inflows triggered by galaxy-galaxy interactions. In fact, the downshift reported for these galaxies is consistent with other observations and simulations, as a result of mergers and/or flybys, which dilute the gas-phase metallicities from metal-poor inflows. The mass of a galaxy cluster appears to be a key variable in determining the importance of environmental effects in the evolution of cluster members, where massive galaxy clusters ($M_ vir M_ odot $) show changes in the slope of the MZR.

AutoSCAN: automatic detection of DBSCAN parameters and efficient clustering of data in overlapping density regions.

The density-based clustering method is considered a robust approach in unsupervised clustering technique due to its ability to identify outliers, form clusters of irregular shapes and automatically determine the number of clusters. These unique properties helped its pioneering algorithm, the Density-based Spatial Clustering on Applications with Noise (DBSCAN), become applicable in datasets where various number of clusters of different shapes and sizes could be detected without much interference from the user. However, the original algorithm exhibits limitations, especially towards its sensitivity on its user input parameters minPts and ɛ. Additionally, the algorithm assigned inconsistent cluster labels to data objects found in overlapping density regions of separate clusters, hence lowering its accuracy. To alleviate these specific problems and increase the clustering accuracy, we propose two methods that use the statistical data from a given dataset's k-nearest neighbor density distribution in order to determine the optimal ɛ values. Our approach removes the burden on the users, and automatically detects the clusters of a given dataset. Furthermore, a method to identify the accurate border objects of separate clusters is proposed and implemented to solve the unpredictability of the original algorithm. Finally, in our experiments, we show that our efficient re-implementation of the original algorithm to automatically cluster datasets and improve the clustering quality of adjoining cluster members provides increase in clustering accuracy and faster running times when compared to earlier approaches.

Waste Management Awareness Education for Elementary School Teachers and Students; the Implementation of Sustainable Environmental Education

In fact, awareness of waste management is still low in Nagari Tanjung Balik, Solok Regency. Based on initial observations, it is known that students at Nagari Tanjung Balik Elementary School do not yet have awareness of waste management. Furthermore, even though since 2022, Nagari Tanjung Balik has had a Waste Bank under the guidance of Universitas Negeri Padang Community Development Team, there has been no contribution from the total of five elementary schools in Nagari Tanjung Balik to the Waste Bank. This is of course not in line with the Nagari Tanjung Balik program which has attempted to intensify waste management in order to create a sustainable environment. Therefore, the solution offered is to provide education to elementary school students who are members of the KKG Cluster III Tanjung Balik Elementary School, X Koto Above District regarding waste management.

An Energy-Efficient Cluster Head Selection and Secure Data Transmission in WSN using Spider Monkey Optimized Algorithm and Hybrid Cryptographic with Security

To conserve energy in wireless sensor networks, clustering is the well-known strategies. However, choosing a cluster head that is energy efficient is crucial for the best clustering. Because data packets must be transmitted between cluster members and the sink node, improper cluster head selection (CHs) uses more energy than other sensor nodes. As a result, it lowers the network's performance and lifespan. Due to the requirement that this network implement appropriate security measures to guarantee secure communication. This paper provides a novel cluster head selection technique that addresses issues of networks’ lives and energy usages using Spider Monkey Optimised Fuzzy C-Means Algorithm (SMOFCM). The CH is chosen using the Spider Monkey Optimisation method in the proposed SMOFCM approach, which builds on the Fuzzy C-means clustering framework. The hybrid cryptographic technique is appropriate for WSN for safe data transmission because it can address sensor challenges such processing power, storage capability, and energy. The Rivest-Shamir-Adleman (RSA), advanced encryption standards (AES), and the suggested algorithm are all used at various stages. Because asymmetric key cryptography makes key management simpler but symmetric key cryptography offers a high level of security. The AES algorithm has been created for phase 1. Phase 2 employed RSA, and all phases were carried out concurrently. According to the simulation results, it reduces energy use, lengthens the network's lifespan, and offers faster encryption, decryption, and execution times for secure data transmission

Obscured star formation in clusters at z = 1.6–2.0: massive galaxy formation and the reversal of the star formation–density relation

ABSTRACT Clusters of galaxies at z $\mathrel {\gtrsim }$ 1 are expected to be increasingly active sites of star formation. To test this, an 850 $\mu$m survey was undertaken of eight clusters at z = 1.6–2.0 using SCUBA-2 on the James Clerk Maxwell Telescope. Mid-infrared properties were used to identify 53 probable counterparts to 45 SCUBA-2 sources with colours that suggested they were cluster members. This uncovered a modest overdensity of 850 $\mu$m sources, with far-infrared luminosities of LIR ≥ 1012 L⊙ (SFR $\mathrel {\gtrsim }$ 100 M⊙ yr−1) and colours consistent with being cluster members, of a factor of 4 ± 1 within the central 1 Mpc radius of the clusters. The submillimetre photometry of these galaxies was used to estimate the total cluster star formation rates. These showed that the mass-normalized rates in the clusters are two orders of magnitude higher than in local systems, evolving as (1 + z)5.5 ± 0.6. This rapid evolution means that the mass-normalized star formation rates in these clusters matched that of average haloes in the field at z ∼ 1.8 ± 0.2 marking the epoch where the local star formation–density relation reverses in massive haloes. The estimated stellar masses of the cluster submillimetre galaxies suggests that their descendants will be amongst the most massive galaxies in z ∼ 0 clusters. This reinforces the suggestion that the majority of the massive early-type galaxy population in z ∼ 0 clusters were likely to have formed at z $\mathrel {\gtrsim }$ 1.5–2 through very active, but dust-obscured, starburst events.

Comprehensive fault diagnosis in UAV-assisted sensor networks: A three-phase automated approach

Ensuring operational safety in an automated working environment is a crucial requirement. In this article, we propose a technique for automated fault diagnosis in unmanned aerial vehicle-based sensor networks (UAV-sensor networks) aimed explicitly at the composite nature of different faults. Our technique consists of 3-stages: (1) UAVs collecting data from sensors and running a modified Z-score statistics to diagnose faulty readings; (2) the UAV cluster head running a multivariate analysis of variance (MANOVA) to identify data faults in cluster members; and (3) utilizing a probabilistic neural network with correlation centroids at the ground control station for further diagnosis of collected UAV data. This approach is intended for progressive improvement in fault diagnosis at different stages of data collection in a UAV-sensor network for critical applications. We conduct an extensive evaluation of our 3-stage approach on the data collected in real-time from the sensors in a physically created UAV-sensor network. The performance of the proposed modified Z-score test improves fault detection accuracy of ∼20.8%, false alarm rate of ∼54.3%, and false positive rate of ∼67.2% with the traditional and existing sensor fault detection approach. The performance of MANOVA to identify the permanent UAV data fault shows fault detection accuracy of ∼10.9%, false alarm rate of ∼44.3%, and false positive rate of ∼48.7% superior to the intermittent and transient faults. Our preliminary results suggest that the proposed approach can handle multiple composite faults and outperforms existing research results.

The treasure behind the haystack: MUSE analysis of five recently discovered globular clusters

Context. After the second data release of Gaia, the number of new globular cluster candidates has increased significantly. However, most of them need to be properly characterised, both spectroscopically and photometrically, by means of radial velocities, metallicities, and deeper photometric observations. Aims. Our goal is to provide an independent confirmation of the cluster nature of Gran 4, a recently discovered globular cluster, with follow-up spectroscopic observations. The derived radial velocity for individual stars, coupled with proper motions, allows us to isolate cluster members from field stars, while the analysis of their spectra allows us to derive metallicities. By including in the analysis the recently confirmed clusters Gran 1, 2, 3, and 5, we aim to completely characterise recently discovered globular clusters. Methods. Using Gaia DR3 and VVV catalogue data and MUSE at VLT observations, we selected cluster members based on their proper motions, radial velocities and their position in colour-magnitude diagrams. Furthermore, full spectral synthesis was performed on the cluster members, extracting surface parameters and metallicity from MUSE spectra. Finally, a completeness estimation was performed on the total globular cluster population of the Milky Way. Results. We confirm the nature of Gran 4, a newly discovered globular cluster behind the Galactic bulge, with a mean radial velocity of RV = −265.28 ± 3.92 km s−1 and a mean metallicity of [Fe/H]= − 1.72 ± 0.32 dex. Additionally, independent measurements of the metallicities were derived for Gran 1, 2, 3, and 5. We also revise the observational lower mass limit for a globular cluster to survive in the bulge and disc environment. We estimate that ∼12 − 26 globular clusters have still to be discovered on the other side of the Galaxy (i.e., behind the bulge, bar and disk), up to 20 kpc.

E-commerce readiness and training needs of small-scale dairy processors in Serbia: Understanding barriers and knowledge gaps

The objective of this study was to identify the requirements needed for selling dairy products through e-commerce, as well as current gaps and challenges that exist for small scale dairy processors (SSDPs), and need to be addressed in order to comply with those requirements. A mixed method research design was used for training needs assessment. Qualitative (in-depth interview with 7 online platform representatives (OPRs)) and quantitative approach (survey questionnaire with 58 SSDPs) were conducted. Interview transcripts were coded and codes were grouped into seven themes. Hierarchical cluster analysis was applied to 146 answers from 58 SSDPs. They were divided into 4 clusters. Mean sums of responses between clusters were compared by Mann-Whitney U test. OPRs suggested that SSDPs should be provided with tools and resources to help them achieve food safety and quality targets, as well as practical knowledge and skills. They reported that it is crucial to find a solution for the cold chain transportation, for maintaining consistent product quality. Survey results showed that SSDPs use kitchen equipment (79.3%) and kitchen cleaning products (81.0%) for dairy processing. In total, 43.1% process raw milk and only 24.1% have product label on the package. Only members of cluster 3 and 4 sell their products online (73.7% and 90.0%, respectively), mostly using their own social media platforms (57.9% and 60.0%, respectively), transporting products to end buyers by themselves in hand refrigerators (47.4% and 70.0%, respectively). By analyzing the differences among clusters of SSDPs, trainings can be tailored to the characteristics and knowledge gaps of each group.

The nature of medium-period variables on the extreme horizontal branch

A fraction of the extreme horizontal branch stars of globular clusters exhibit a periodic light variability that has been attributed to rotational modulation caused by surface spots. These spots are believed to be connected to inhomogeneous surface distribution of elements. However, the presence of such spots has not been tested against spectroscopic data. We analyzed the phase-resolved ESO X-shooter spectroscopy of three extreme horizontal branch stars that are members of the globular cluster ω Cen and also display periodic light variations. The aim of our study is to understand the nature of the light variability of these stars and to test whether the spots can reproduce the observed variability. Our spectroscopic analysis of these stars did not detect any phase-locked abundance variations that are able to reproduce the light variability. Instead, we revealed the phase variability of effective temperature and surface gravity. In particular, the stars show the highest temperature around the light maximum. This points to pulsations as a possible cause of the observed spectroscopic and photometric variations. However, such an interpretation is in a strong conflict with Ritter’s law, which relates the pulsational period to the mean stellar density. The location of the ω Cen variable extreme horizontal branch stars in HR diagram corresponds to an extension of PG 1716 stars toward lower temperatures or blue, low-gravity, large-amplitude pulsators toward lower luminosities, albeit with much longer periods. Other models of light variability, namely, related to temperature spots, should also be tested further. The estimated masses of these stars in the range of 0.2–0.3 M⊙ are too low for helium-burning objects.

High-resolution spectroscopy of the young open cluster M 39 (NGC 7092)

M 39 is a nearby young open cluster hardly studied in the last few decades. No giant is known among its members and its chemical composition has never been studied. In order to investigate it, we performed high-resolution spectroscopy of 20 expected cluster members with the HARPS and FIES spectrographs. By combining our observations with archival photometry and Gaia-DR3 data we searched for evolved members and studied cluster properties such as the radial velocity, extinction, and age. For the first time, we provide stellar parameters and chemical abundances for 21 species with atomic numbers up to 56. We have not found any new giant as a likely member and we notice a negligible reddening along the cluster field, which we place at 300 pc. We obtain a mean radial velocity for M 39 of −5.5 ± 0.5 km s−1 and an isochrone-fitting age of 430 ± 110 Ma, which corresponds to a MSTO mass of around 2.8 M⊙. This value is consistent with the Li content and chromospheric activity shown by its members. Based on main-sequence stars, the cluster exhibits a solar composition, [Fe/H] = +0.04 ± 0.08 dex, compatible with its Galactocentric location. However, it has a slightly subsolar abundance of Na and an enriched content of neutron-capture elements, specially Ba. In any case, the chemical composition of M 39 is fully compatible with that shown by other open clusters that populate the Galactic thin disc.

Discovery of Astrometric Accelerations by Dark Companions in the Globular Cluster ω Centauri

We present results from the search for astrometric accelerations of stars in ω Centauri using 13 yr of regularly scheduled Hubble Space Telescope WFC3/UVIS calibration observations in the cluster core. The high-precision astrometry of ∼160,000 sources was searched for significant deviations from linear proper motion. This led to the discovery of four cluster members and one foreground field star with compelling acceleration patterns. We interpreted them as the result of the gravitational pull by an invisible companion and determined preliminary Keplerian orbit parameters, including the companion’s mass. For the cluster members, our analysis suggests periods ranging from 8.8 to 19+ yr and dark companions in the mass range of ∼0.7 to ∼1.4M ☉. At least one companion could exceed the upper mass boundary of white dwarfs and can be classified as a neutron star candidate.

Cluster stability-driven optimization for enhanced routing in heterogeneous vehicular networks

The new era of the Internet of Things is promoting the evolution of self-driving vehicles into connected and autonomous vehicles (CAVs). The deployment of CAVs in smart cities is highly dependent on the performance of their underlying networks known as vehicular networks. Designing an effective clustering approach is of great importance in such dynamic networks as it can significantly improve the reliability and scalability of the routing protocols. In this paper, we consider a heterogeneous vehicular network architecture that supports vehicle-to-vehicle and vehicle-to-infrastructure communications based on IEEE 802.11p and cellular networks (LTE/5G) with direct communications, namely cellular vehicle-to-everything (C-V2X) technologies. We introduce a novel clustering scheme for real-time routing based on the proposed network architecture. We formulate the problem of optimal clustering for connected and autonomous vehicles (OCCAV) and show that the problem is NP-hard. We then develop a clusters' stability maximization algorithm (CSM), which utilizes the stability degree of vehicles over a prediction horizon to efficiently solve the optimization problem in real-time. The algorithm is used within a rolling horizon framework for continuously solving the problem, making the resulting clusters adaptive to future traffic dynamics. We propose a hybrid routing protocol based on our clustering scheme, aiming to improve the packet delivery ratio and reduce the average delivery delay. For evaluation purposes, we use extensive realistic simulations based on mobility scenarios validated using real vehicular trajectories. The results demonstrate that our clustering scheme improves the alternative algorithms in terms of the average cluster head duration, cluster head change rate, cluster member duration, and overall stability by 61%, 62%, 44%, and 52%, respectively. CSM also outperforms clustering overhead by 54%. Compared to the other cluster-based routing, our scheme also achieves a higher packet delivery ratio by up to 30%, and a lower average delay by up to 52%. To provide an in-depth analysis of the optimality of our scheme and its alternatives, we also use the Gurobi optimizer to find an optimal solution to the OCCAV problem. The results suggest that our scheme can achieve near-optimal cluster stability.

Optimization Algorithm for AoI-Based UAV-Assisted Data Collection

Regarding the issue of information freshness in systems that aid in data collection using unmanned aerial vehicles (UAVs), a data collection algorithm that is based on freshness and UAV assistance is proposed. Under the limitations of wireless sensor node communication distance and UAV parameters, the optimization problem of minimizing the average spatial correlation age of information (SCAoI) of all nodes in the area is set up. This problem is solved by optimizing the number of clusters, UAV flight trajectories, and the order of data collection from cluster member nodes. The maximum communication distance of the nodes is used as the cluster formation radius, and the maximum-minimum distance clustering algorithm is used to cluster the nodes in the region to obtain the minimum number of clusters. After it has been proven that the trajectory optimization problem in this study is NP-hard, the ant colony algorithm is applied to obtain the minimum flight time and the corresponding trajectory. By using the greedy algorithm to determine the member nodes in the sequence of data collection for a cluster, the instantaneous SCAoI of the UAV arriving at the cluster head is solved. Simulation results show that the proposed algorithm in this paper can effectively improve the freshness of data and reduce the average SCAoI of the system compared with the algorithm in the comparative literature, reducing the average SCAoI by about 61%.

Variable stars in galactic globular clusters. I. The population of RR Lyrae stars

We present a comprehensive catalog of $2824$ RR Lyrae stars (RRLs) residing in $115$ Galactic globular clusters (GCs). Our catalog includes 1594 fundamental-mode (RRab), 824 first-overtone (RRc), and 28 double-mode (RRd) RRLs, as well as 378 RRLs of an unknown pulsation mode. We cross-matched 481\,349 RRLs reported in the third data release (DR3) of the ESA mission and the literature to 170 known GCs. Membership probabilities were computed as the products of a position and shape-dependent prior and a likelihood was computed using parallaxes, proper motions, and, where available, radial velocities from Membership likelihoods of RRLs were computed by comparing cluster average parameters based on known member stars and the cross-matched RRLs. We determined empirical RRL instability strip (IS) boundaries based on our catalog and detected three new cluster RRLs inside this region via their excess $G-$band photometric uncertainties. We find that $77<!PCT!>$ of RRLs in GCs are included in the DR3 Specific Object Study, and $82<!PCT!>$ were classified as RRLs by the DR3 classifier, with the majority of the missing sources being located at the crowded GC centers. Surprisingly, we find that $25<!PCT!>$ of cluster member stars located within the empirical IS are not RRLs and appear to be non-variable. Additionally, we find that $80<!PCT!>$ of RRab, $84<!PCT!>$ of RRc, and $100<!PCT!>$ of the RRd stars are located within theoretical IS boundaries predicted using MESA models with $Z=0.0003$, $M=0.7$ \(M_ and $Y=0.290$. Unexpectedly, a higher $Y=0.357$ is required to fully match the location of RRc stars, and lower $Y=0.220$ is needed to match the location of RRab stars. Lastly, our catalog does not exhibit an Oosterhoff dichotomy, with at least 22 GCs located inside the Oosterhoff "gap," which is close to the mode of the distribution of mean RRL periods in GCs.

A statistical and multiwavelength photometric analysis of a young embedded open star cluster: IC 1590

ABSTRACT We present a statistical and multiwavelength photometric studies of young open cluster IC 1590. We identified 91 cluster members using Gaia DR3 astrometry data using ensemble-based unsupervised machine learning techniques. From Gaia EDR3 data, we estimate the best-fitting parameters for IC 1590 using the Automated Stellar Cluster Analysis package (asteca) yielding the distance d ∼ 2.87 ± 0.02 kpc, age ∼ 3.54 ± 0.05 Myr, metallicity z ∼ 0.0212 ± 0.003, binarity value of ∼ 0.558, and extinction Av ∼ 1.252 ± 0.4 mag for an Rv value of ∼ 3.322 ± 0.23. We estimate the initial mass function slope of the cluster to be α = 1.081 ± 0.112 for single stars and α = 1.490 ± 0.051 for a binary fraction of ∼ 0.558 in the mass range 1 M⊙ ≤ m (M⊙) ≤ 100 M⊙. The G-band luminosity function slope is estimated to be ∼ 0.33 ± 0.09. We use (J − H) versus (H − Ks) colour–colour diagram to identify young stellar objects (YSOs). We found that all the identified YSOs have ages ≤ 2 Myr and masses ∼ 0.35 – 5.5 M⊙. We also fit the radial surface density profile. Using the galpy, we performed orbit analysis of the cluster. The extinction map for the cluster region has been generated using the PNICER technique, and it is almost similar to the dust structure obtained from the 500 μm dust continuum emissions map of Herschel SPIRE. We finally at the end discussed the star formation scenario in the cluster region.

Binary Fraction in Galactic Star Clusters: FSR 866, NGC 1960, and STOCK 2

The study of binary stars in different astronomical environments offers insights into the dynamical state of the hosting stellar systems. The binary fraction in fact plays a crucial role in the dynamical evolution of stellar systems, regulating processes like mass segregation and dynamical heating, and in some cases leading to the formation of exotic objects, like, for instance, blue straggler stars. We used two methodologies to estimate the binary fraction in three different-age open star clusters: FSR 866, NGC 1960 (M36), and Stock 2. The first is a photometric approach based on color–magnitude diagram analysis, and the second is a spectroscopic technique that employs radial velocity measurements. We used Gaia DR3 data in tandem with new spectroscopic observations, and employed the Density-Based Spatial Clustering of Applications with Noise algorithm to identify probable cluster members based on proper motion and parallax in 3D space. The new sample of cluster members allows us to provide new estimates of the cluster fundamental parameters. As a by-product, we found two previously undetected, small physical groups of stars in the background of NGC 1960. The resulting binary fractions lie in the range 0.3–0.5 and are in good agreement with those expected theoretically for open clusters.

The Optical Properties of Galaxy Cluster Abell 2319

The optical photometric and spectroscopic investigations of the massive and merging galaxy cluster Abell 2319 (A2319) are presented here. RTT150 telescope of TÜBİTAK, Antalya, Türkiye used CCD imaging and spectroscopic observations. In this paper, 110 galaxies were determined in A2319 and defined as the magnitudes of the Bessel B and R filters in each cluster member galaxy. Spectral observations were done of the brightest cluster galaxy (BCG) and six additional brilliant galaxies. We estimated the Luminosity Function (LF) of galaxies for each filter. The resulting LF of cluster galaxies for each filter is well-fitted by the Double Schechter function. The best-fit parameter values derived as the characteristic absolute magnitudes are -21.08 ± 0.03, and -20.84 ± 0.01, -21.43 ± 0.02, and -20.54 ± 0.02, and the slopes at the faint end of the LF were -1.34 ± 0.04 and -1.12 ± 0.03, -1.47 ± 0.05 and -1.18 ± 0.03 for B and R filters, respectively.

Caenorhabditis elegans immune responses to microsporidia and viruses

The model organism Caenorhabditis elegans is susceptible to infection by obligate intracellular pathogens, specifically microsporidia and viruses. These intracellular pathogens infect intestinal cells, or, for some microsporidia, epidermal cells. Strikingly, intestinal cell infections by viruses or microsporidia trigger a common transcriptional response, activated in part by the ZIP-1 transcription factor. Among the strongest activated genes in this response are ubiquitin-pathway members and members of the pals family, an intriguing gene family with cross-regulations of different members of genomic clusters. Some of the induced genes participate in host defense against the pathogens, for example through ubiquitin-mediated inhibition. Other mechanisms defend the host specifically against viral infections, including antiviral RNA interference and uridylation. These various immune responses are altered by environmental factors and by intraspecific genetic variation of the host. These pathogens were first isolated 15 years ago and much remains to be discovered using C. elegans genetics; also, other intracellular pathogens of C. elegans may yet to be discovered.