Intermediate Clusters Research Articles

A closer look at the binary content of NGC 1850

ABSTRACT Studies of young clusters have shown that a large fraction of O-/early B-type stars are in binary systems, where the binary fraction increases with mass. These massive stars are present in clusters of a few Myr, but gradually disappear for older clusters. The lack of detailed studies of intermediate-age clusters has meant that almost no information is available on the multiplicity properties of stars with $M\lt 4\, {\rm M}_{\odot }$. In this study we present the first characterization of the binary content of NGC 1850, a 100 Myr-old massive star cluster in the Large Magellanic Cloud, relying on a VLT/MUSE multi-epoch spectroscopic campaign. By sampling stars down to M = 2.5 M⊙, we derive a close binary fraction of 24 ± 5 per cent in NGC 1850, in good agreement with the multiplicity frequency predicted for stars of this mass range. We also find a trend with stellar mass (magnitude), with higher mass (brighter) stars having higher binary fractions. We modelled the radial velocity curves of individual binaries using the joker and constrained the orbital properties of 27 systems, ∼17 per cent of all binaries with reliable radial velocities in NGC 1850. This study has brought to light a number of interesting objects, such as four binaries showing mass functions f(M) > 1.25 M⊙. One of these, star #47, has a peculiar spectrum, explainable with the presence of two discs in the system, around the visible star and the dark companion, which is a black hole candidate. These results confirm the importance and urgency of studying the binary content of clusters of any age.

An Improved Search Algorithm for WSN with Charging Nodes

The existing semi-centralized stochastic election approach, Stochastic Election of Appropriate Range Cluster Heads (SEARCH) is analyzed and features are improved which, boasts low time cost, improved stable period, and eliminates the unfavorable scenario, that no cluster head emerges during some specific rounds. However, the implementation of SEARCH in WSNs with solar charging nodes offers very marginal improvement in a stable period. This proves the inefficiency of the algorithm in handling these charging nodes. The improvement offered aims to make the algorithm, more energy aware and hence comparatively well organized in handling the charging nodes in the network. This improvement, equipped with dynamic tracking of instantaneous node energy shows a promising way to extend clustering algorithms to networks with chargeable nodes. In addition, the existing SEARCH algorithm’s cluster head election procedure lacks a futuristic view of the minimum energy requirement for successful operation throughout an entire round. Intermediate cluster head death can be detrimental, to network performance by paralyzing the corresponding clusters, resulting in total data transmission failure of all nodes in that cluster. Implementing the improved SEARCH algorithm drastically reduces the bit loss by 95%, with increasing the transmitted bits successfully by 4%. The overall lifetime of the WSN improves by around 30% and the number of cluster heads dying prematurely in the middle of round operation is reduced by 89%. This paper analyzes and refines a current clustering algorithm, thereby promisingly enhancing its capacity to boost the overall network performance.

Hubble Space Telescope survey of Magellanic Cloud star clusters: UV-dim stars in young clusters

ABSTRACT Young and intermediate-age star clusters of both Magellanic Clouds exhibit complex colour–magnitude diagrams. In addition to the extended main-sequence turn-offs (eMSTOs), commonly observed in star clusters younger than ∼2 Gyr, the clusters younger than ∼800 Myr exhibit split main sequences (MSs). These comprise a blue MS, composed of stars with low rotation rates, and a red MS, which hosts fast-rotating stars. While it is widely accepted that stellar populations with different rotation rates are responsible for the eMSTOs and split MSs, their formation and evolution are still debated. A recent investigation of the ∼1.7-Gyr-old cluster NGC 1783 detected a group of eMSTO stars extremely dim in ultraviolet (UV) bands. Here, we use multiband Hubble Space Telescope photometry to investigate five star clusters younger than ∼200 Myr, including NGC 1805, NGC 1818, NGC 1850, and NGC 2164 in the Large Magellanic Cloud, and the Small Magellanic Cloud cluster NGC 330. We discover a group of bright MS stars in each cluster that are significantly dim in the F225W and F275W bands, similar to what is observed in NGC 1783. Our result suggests that UV-dim stars are common in young clusters. The evidence that most of them populate the blue MS indicates that they are slow rotators. As a by-product, we show that the star clusters NGC 1850 and BHRT 5b exhibit different proper motions, thus corroborating the evidence that they are not gravitationally bound.

Understanding heterogeneity of human bone marrow plasma cell maturation and survival pathways by single-cell analyses

Human bone marrow (BM) plasma cells are heterogeneous, ranging from newly arrived antibody-secreting cells (ASCs) to long-lived plasma cells (LLPCs). We provide single-cell transcriptional resolution of 17,347 BM ASCs from five healthy adults. Fifteen clusters are identified ranging from newly minted ASCs (cluster 1) expressing MKI67 and high major histocompatibility complex (MHC) class II that progress to late clusters 5-8 through intermediate clusters 2-4. Additional ASC clusters include the following: immunoglobulin (Ig) M predominant (likely of extra-follicular origin), interferon responsive, and high mitochondrial activity. Late ASCs are distinguished by G2M checkpoints, mammalian target of rapamycin (mTOR) signaling, distinct metabolic pathways, CD38 expression, utilization of tumor necrosis factor (TNF)-receptor superfamily members, and two distinct maturation pathways involving TNF signaling through nuclear factor κB (NF-κB). This study provides a single-cell atlas and molecular roadmap of LLPC maturation trajectories essential in the BM microniche. Altogether, understanding BM ASC heterogeneity in health and disease enables development of new strategies to enhance protective ASCs and to deplete pathogenic ones.

Asteroseismic age constraints on the open cluster NGC 2477 using oscillating stars identified with TESS FFI

Context. Asteroseismology is one of the few methods to derive ages of individual stars due to the high precision of their observations. Isochrone fitting is a powerful alternative method for deriving ages by studying clusters of stars. Pulsating stars in clusters should therefore allow for detailed studies of the stellar models. Aims. Our objectives are to exploit the NASA TESS data along with ESA Gaia data to search for and detect oscillations in cluster member stars. We analyse the intermediate-age open cluster NGC 2477, known to suffer from differential extinction, to explore if asteroseismology and cluster characteristics can help us understand the metallicity and extinction, as well as result in better age determinations than isochrone-fitting alone. Methods. We combined a multitude of recent observations from Gaia, high-resolution spectroscopy, and extinction maps to analyse the cluster and then search for and detect variability in the member stars using TESS full frame images (FFIs) data. To interpret all of these data, we used stellar structure, evolution and oscillation codes. Results. We conducted an in-depth analysis of the extinction and metallicity of NGC 2477, using the most recent spectroscopic, photometric, and extinction observations for the cluster. Analysis of dust and extinction maps confirmed that the differential extinction in the direction of the cluster is not due to the background. The cluster’s metallicity from high-resolution spectroscopy varies from 0.06 to 0.16 dex. We performed an isochrone fitting to the cluster using publically available isochrones (BASTI, MIST, and PARSEC), which provides a cluster age of between 0.6 to 1.1 Ga. Then using TESS FFI, we analysed the time dimension of the members of this cluster. We created optimised pixel light curves using the tessipack package which allows us to consider possible contamination by nearby stars. Using these light curves, we identified many interesting levels of variability of stars in this cluster, including binaries and oscillating stars. For the asteroseismic analysis, we selected a few uncontaminated A–F type oscillating stars and used the MESA and GYRE codes to interpret the frequency signals. By comparing the theoretical and the observed spectra, we identified frequency separations, Δν, for four stars. Then using the identified Δν and imposing that the best matched theoretical models have the same age, metallicity, and background extinction, we constrained the cluster’s age to 1.0 ± 0.1 Ga. Conclusions. We conclude that using the TESS FFI data, we can identify oscillating stars in clusters and constrain the age of the cluster using asteroseismology.

Matched-Decision AP Selection for User-Centric Cell-Free Massive MIMO Networks

This work proposes a scalable access point (AP) selection framework based on a competitive mechanism that operates in two stages. Initially, the user equipment (UE) connects to an intermediate AP cluster, where a matched-decision among the APs and UEs establishes the best connection in terms of large-scale fading and prevents UEs from being dropped. Then, UEs can expand their AP clusters by connecting to more APs. We compare our method with baseline solutions considering different precoding techniques in centralized and distributed network implementations. We propose three strategies to fine-tune the AP clusters, reducing the number of UEs per AP without compromising the spectral efficiency (SE) or improving energy efficiency. The simulations comprise a range of UEs and APs, the number of antennas per AP varies, and each AP can serve a limited number of UEs. The results show that our solution improves up to 163% the SE of the 95% likely UEs compared with baseline solutions and that the number of UEs each AP serves is crucial for improving SE. Additional results indicate that our solution allows APs to save processing to enhance SE and evidence that the number of APs affects the SE differently in each network implementation.

Single-nucleus RNA sequencing of human pancreatic islets identifies novel gene sets and distinguishes β-cell subpopulations with dynamic transcriptome profiles

BackgroundSingle-cell RNA sequencing (scRNA-seq) provides valuable insights into human islet cell types and their corresponding stable gene expression profiles. However, this approach requires cell dissociation that complicates its utility in vivo. On the other hand, single-nucleus RNA sequencing (snRNA-seq) has compatibility with frozen samples, elimination of dissociation-induced transcriptional stress responses, and affords enhanced information from intronic sequences that can be leveraged to identify pre-mRNA transcripts.MethodsWe obtained nuclear preparations from fresh human islet cells and generated snRNA-seq datasets. We compared these datasets to scRNA-seq output obtained from human islet cells from the same donor. We employed snRNA-seq to obtain the transcriptomic profile of human islets engrafted in immunodeficient mice. In both analyses, we included the intronic reads in the snRNA-seq data with the GRCh38-2020-A library.ResultsFirst, snRNA-seq analysis shows that the top four differentially and selectively expressed genes in human islet endocrine cells in vitro and in vivo are not the canonical genes but a new set of non-canonical gene markers including ZNF385D, TRPM3, LRFN2, PLUT (β-cells); PTPRT, FAP, PDK4, LOXL4 (α-cells); LRFN5, ADARB2, ERBB4, KCNT2 (δ-cells); and CACNA2D3, THSD7A, CNTNAP5, RBFOX3 (γ-cells). Second, by integrating information from scRNA-seq and snRNA-seq of human islet cells, we distinguish three β-cell sub-clusters: an INS pre-mRNA cluster (β3), an intermediate INS mRNA cluster (β2), and an INS mRNA-rich cluster (β1). These display distinct gene expression patterns representing different biological dynamic states both in vitro and in vivo. Interestingly, the INS mRNA-rich cluster (β1) becomes the predominant sub-cluster in vivo.ConclusionsIn summary, snRNA-seq and pre-mRNA analysis of human islet cells can accurately identify human islet cell populations, subpopulations, and their dynamic transcriptome profile in vivo.

Galaxy clusters in the Vela Supercluster – I. Deep NIR catalogues

ABSTRACT We present six deep Near-InfraRed (JHKs) photometric catalogues of galaxies identified in six cluster candidates (VC02, VC04, VC05, VC08, VC10, and VC11) within the Vela Supercluster (VSCL) as part of our efforts to learn more about this large supercluster, which extends across the zone of avoidance (ℓ = 272.°5 ± 20°, b = ±10°, at cz ∼ 18 000 km s−1). The observations were conducted with the InfraRed Survey Facility (IRSF), a 1.4-m telescope situated at the South African Astronomical Observatory (SAAO) in Sutherland. The images in each cluster cover $\sim 80{{\ \rm per\ cent}}$ of their respective Abell radii. We identified a total number of 1715 galaxies distributed over the six cluster candidates, of which only $\sim 15{{\ \rm per\ cent}}$ were previously known. We study the structures and richnesses of the six clusters out to the cluster-centric completeness radius of rc < 1.5 Mpc and magnitude completeness limit of $K_s^o\lt 15{_{.}^{\rm m}}5$, using their iso-density contour maps and radial density profiles. The analysis shows VC04 to be the richest of the six. It is a massive cluster comparable to the Coma and Norma clusters, although its velocity dispersion, σv = 455 km s−1, seems rather low for a rich cluster. VC02 and VC05 are found to be relatively rich clusters while VC08 is rather poor. Also, VC05 has the highest central number density among the six. VC11 is an intermediate cluster that contains two major subclusters while VC10 has a filament-like structure and is likely not to be a cluster after all.

Exploration of the Atomic Pathway of Seed-Mediated Growth from Icosahedral [Au25(SR)18]− to Bi-Icosahedral Au38(SR)24 and Au44(SR)26 Clusters Based on the 2e– Hopping Mechanism

Size growth is ubiquitous in the gold nanocluster synthesis. However, the atomic-level mechanism of seed-mediated growth of gold clusters remains mysterious. In this study, the seed-mediated growth pathway from the icosahedral [Au25(SR)18]- cluster to the bi-icosahedral Au38(SR)24 and Au44(SR)26 clusters is studied based on the two-electron (2e-) hopping mechanism. First, atomic structures of three key intermediate clusters, [Au29(SR)20]-, [Au33(SR)22]-, and Au41(SR)25, are predicted based on the 2e--unit decomposition strategy. The theoretically simulated UV-Vis spectra based on the predicted structure model of [Au29(SR)20]- and [Au33(SR)22]- matched well with the experimental curves reported previously. Based on the predicted intermediate cluster structures, the size growth pathway from the eight-electron (8e-) [Au25(SR)18]- cluster to 14-electron (14e-) Au38(SR)24 and 18-electron (18e-) Au44(SR)26 clusters is determined. In the step of formation of bi-icosahedral Au38(SR)24 from icosahedral [Au25(SR)18]-, two Au4 units are first formed. The third 2e- hopping step results in formation of an icosahedron unit. The present studies offered new insights into the formation and size conversion mechanism of ligand-protected gold nanoclusters containing icosahedral cores.

Multivariate roles of litter traits on moisture and flammability of temperate northeastern North American tree species

BackgroundTree litter is the primary fuel affecting surface fire behavior in most fire-prone forest and woodland ecosystems in northeastern North America. Fire exclusion and land use changes have dramatically altered fire regimes in many of these ecosystems, shifting toward species that reinforce the continued diminution of fire. Comparative litter flammability studies provide a useful approach to identify the corresponding leaf and litter bed traits that drive the positive feedback termed “mesophication” in these ecosystems.ResultsIn this study, we measured laboratory flammability and moisture characteristics of leaf litter from 17 common tree species in temperate forests of northeastern North America. Principal components analysis of flammability and moisture data resulted in species separating along a pyrophyte-to-mesophyte gradient. Pyrophytic Quercus litter was the most flammable of all species, and Pinus litter dried the most rapidly and flamed for the longest duration. The remaining mesophytic species grouped into either a high moisture retention-poor burning cluster (Acer rubrum, Betula alleghaniensis, Nyssa sylvatica, Carya glabra, C. tomentosa) or an intermediate flammability cluster (Acer saccharum, C. ovata, Tilia americana). Several litter traits were associated with multivariate factors. Leaf length, density, curling, surface area-to-volume, and litter bed bulk density were associated with the factor comprising saturation moisture content, flaming time, and consumption. Specific leaf area was related to moisture time-lag and flame height. Litter bed packing ratio was most related to smoldering duration.ConclusionsInterspecific variability in leaf and litter bed traits explained substantial differences in moisture dynamics and flammability among the species examined. These findings extend our understanding of litter traits’ influence on the combustion environment and affirm the potential effects of pyrophytic and mesophytic tree species on contemporary fire regimes in northeastern North American forests.

Intermediate Cluster Disinfection: Which Disinfection Solution Is Most Effective on Milking Liners? A Comparison of Microorganism Reduction on Liner Inner Surfaces Using Quantitative Swab Sampling Technique.

During machine milking, pathogenic microorganisms can be transmitted from cow to cow through liners. Therefore, in Germany, a spray method for the intermediate disinfection of the milking cluster is often used for prevention. This method of cluster disinfection is easy to perform, requires little time and no extra materials, and the disinfection solution is safe from outside contamination in the spray bottle. Since no data on a systematic efficacy trial are available, the aim of this study was to determine the microbial reduction effect of intermediate disinfection. Therefore, laboratory and field trials were conducted. In both trials, two sprays of 0.85 mL per burst of different disinfectant solutions were sprayed into the contaminated liners. For sampling, a quantitative swabbing method using a modified wet-dry swab (WDS) technique based on DIN 10113-1: 1997-07 was applied. Thus, the effectiveness of disinfectants based on Peracetic Acid, Hydrogen Peroxide and Plasma-Activated Buffered Solution (PABS) was compared. In the laboratory trial, the inner surfaces of liners were contaminated with pure cultures of Escherichia (E.) coli, Staphylococcus (S.) aureus, Streptococcus (Sc.) uberis and Sc. agalactiae. The disinfection of the contaminated liners with the disinfectants resulted in a significant reduction in bacteria with values averaging 1 log for E. coli, 0.7 log for S. aureus, 0.7 log for Sc. uberis and 0.8 log for Sc. agalactiae. The highest reduction was obtained for contamination with E. coli (1.3 log) and Sc. uberis (0.8 log) when PABS was applied and for contamination with S. aureus (1.1 log) and Sc. agalactiae (1 log) when Peracetic Acid Solution (PAS) was used. Treatment with sterile water only led to an average reduction of 0.4 log. In the field trial, after the milking of 575 cows, the liners were disinfected and the total microorganism count from the liner surface was performed. The reduction was measured against an untreated liner within the cluster. Although a reduction in microorganisms was achieved in the field trial, it was not significant. When using PAS, a log reduction of 0.3 was achieved; when using PABS, a log reduction of 0.2 was obtained. The difference between the two disinfection methods was also not significant. Treatment with sterile water only led to a reduction of 0.1 log. The results show that spray disinfection under these circumstances does result in a reduction in the bacteria on the milking liner surface, but for effective disinfection a higher reduction would be preferred.

Broken bond models, magic-sized clusters, and nucleation theory in nanoparticle synthesis.

Magic clusters are metastable faceted nanoparticles that are thought to be important and, sometimes, observable intermediates in the nucleation of certain faceted crystallites. This work develops a broken bond model for spheres with a face-centered-cubic packing that form tetrahedral magic clusters. With just one bond strength parameter, statistical thermodynamics yield a chemical potential driving force, an interfacial free energy, and free energy vs magic cluster size. These properties exactly correspond to those from a previous model by Mule et al. [J. Am. Chem. Soc. 143, 2037 (2021)]. Interestingly, a Tolman length emerges (for both models) when the interfacial area, density, and volume are treated consistently. To describe the kinetic barriers between magic cluster sizes, Mule et al. invoked an energy parameter to penalize the two-dimensional nucleation and growth of new layers in each facet of the tetrahedra. According to the broken bond model, barriers between magic clusters are insignificant without the additional edge energy penalty. We estimate the overall nucleation rate without predicting the rates of formation for intermediate magic clusters by using the Becker-Döring equations. Our results provide a blueprint for constructing free energy models and rate theories for nucleation via magic clusters starting from only atomic-scale interactions and geometric considerations.

UOCS-IX. AstroSat/UVIT Study of the Open Cluster NGC 2818: Blue Stragglers, Yellow Stragglers, Planetary Nebula, and their Membership

We present the first far-UV (FUV) imaging results of the intermediate-age Galactic open cluster NGC 2818 that has a planetary nebula (PN) within the field using images taken from the Ultra Violet Imaging Telescope (UVIT) aboard AstroSat. We identify cluster members by combining UVIT-detected sources with Gaia EDR3 data. We detect four bright and hot blue straggler stars (BSSs) and two yellow straggler stars (YSSs) based on their location in optical and FUV–optical color–magnitude diagrams. Based on the parameters estimated using spectral energy distributions, we infer that BSSs are either collisional products or might have undetectable white dwarf (WD) companions. Our photometric analysis of YSSs confirms their binarity, consistent with the spectroscopic results. We find YSSs to be formed through a mass-transfer scenario and the hot components are likely to be A-type subdwarfs. A comparison of the radial velocity, Gaia EDR3 proper motion of the PN with the cluster, and reddening toward the PN and the cluster does not rule out the membership of the PN. Comparing the central star’s position with theoretical post‐AGB (pAGB) models suggest that it has already entered the WD cooling phase, and its mass is deduced to be ∼0.66 M ⊙. The corresponding progenitor mass turns out to be ∼2.1 M ⊙, comparable to the turn-off mass of the cluster, implying that the progenitor could have formed in the cluster. We suggest that the NGC 2818 might be one of the few known clusters to host a PN, providing a unique opportunity to test stellar evolution models.

Thymic Epithelial Tumors: An Evolving Field.

Despite their rarity, thymic epithelial tumors (TETs) have attracted much interest over the years, leading to an impressive number of histological and staging classifications. At present, TETs are divided by the WHO classification into four main subtypes: type A, type AB, and type B thymomas (subdivided into B1, B2, and B3), and thymic carcinomas, going from the more indolent to the most aggressive ones. Among many debated staging proposals, the TNM and the Masaoka-Koga staging systems have been widely accepted and used in routine practice. The four-tiered histological classification is symmetrically mirrored by the molecular subgrouping of TETs, which identifies an A-like and an AB-like cluster, with frequent GTF2I and HRAS mutations; an intermediate B-like cluster, with a T-cell signaling profile; and a carcinoma-like cluster comprising thymic carcinomas with frequent CDKN2A and TP53 alterations and a high tumor molecular burden. Molecular investigations have opened the way to tailored therapies, such as tyrosine kinase inhibitors targeting KIT, mTOR, and VEGFR, and immune-checkpoints that have been adopted as second-line systemic treatments. In this review, we discuss the crucial events that led to the current understanding of TETs, while disclosing the next steps in this intriguing field.

The Ovule Number Variation Provides New Insights into Taxa Delimitation in Willows (Salix subgen. Salix; Salicaceae).

Salix babylonica, S. alba and S. fragilis are closely related species characterized by the lanceolate, acuminate and serrulate leaves. The boundaries between them are defined by relatively few diagnostic characters, and their identification is not fully solved. Recent studies have demonstrated that the number of ovules present in the ovaries of the willow flower can assist in the identification of the species. The detailed ovule data, characteristic for flowers of each species, S. babylonica, S. alba and S. fragilis, and variation in the number of ovules per ovary were documented using many representatives of these species from various geographic regions. The data included the minimum and maximum number of ovules per valve and per ovary and the percentages of valves with a specific number of ovules in a catkin. Some intermediate genotypes and clusters with similar ovule indexes were observed. The important character for the identification of S. babylonica was the presence of valves with 1 or 2 ovules in the ovaries; S. fragilis had valves with 3 ovules while S. alba had the greater number (4-12).

Identifying pathways between psychiatric symptoms and psychosocial functioning in the general population

The present study aims to identify pathways between psychiatric network symptoms and psychosocial functioning and their associated variables among functioning clusters in the general population. A cross-sectional web-based survey was administered in a total of 3,023 individuals in Brazil. The functioning clusters were derived by a previous study identifying three different groups based on the online Functioning Assessment Short Test. Networking analysis was fitted with all items of the Patient-Reported Outcomes Measurement Information System for depression and for anxiety (PROMIS) using the mixed graphical model. A decision tree model was used to identify the demographic and clinical characteristics of good and low functioning. A total of 926 (30.63%) subjects showed good functioning, 1,436 (47.50%) participants intermediate functioning, and 661 (21.86%) individuals low functioning. Anxiety and uneasy symptoms were the most important nodes for good and intermediate clusters but anxiety, feeling of failure, and depression were the most relevant symptoms for low functioning. The decision tree model was applied to identify variables capable to discriminate individuals with good and low functioning. The algorithm achieved balanced accuracy 0.75, sensitivity 0.87, specificity 0.63, positive predictive value 0.63 negative predictive value 0.87 (p<0.001), and an area under the curve of 0.83 (95%CI:0.79–0.86, p<0.01). Our results show that individuals who present psychological distress are more likely to experience poor functional status, suggesting that this subgroup should receive a more comprehensive psychiatric assessment and mental health care.

Genetic and Structural Brain Correlates of Cognitive Subtypes Across Youth at Family Risk for Schizophrenia and Bipolar Disorder.

Cognitive impairment is an important feature of Schizophrenia (SZ) and Bipolar Disorder (BP) with severity across the two disorders characterized by significant heterogeneity. Youth at family risk for SZ and BP were clustered based on cognitive function and examined in terms of the clinical, genetic, and brain imaging correlates of cluster membership. One hundred sixty participants, 32 offspring of patients with SZ, 59 offspring of patients with BP and 69 offspring of healthy control parents underwent clinical and cognitive assessments, genotyping and structural MRI. K-means clustering was used to group family risk participants based on cognitive measures. Clusters were compared in terms of cortical and subcortical brain measures as well as polygenic risk scores. Participants were grouped in 3 clusters with intact, intermediate, and impaired cognitive performance. The intermediate and impaired clusters had lower total brain surface area compared with the intact cluster, with prominent localization in frontal and temporal cortices. No between-cluster differences were identified in cortical thickness and subcortical brain volumes. The impaired cluster also had poorer psychosocial functioning and worse PRS-COG compared with the other 2 clusters and with offspring of healthy control parents, while there was no significant between-cluster difference in terms of PRS-SZ and PRS-BP. PRS-COG predicted psychosocial functioning, yet this effect did not appear to be mediated by an effect of PRS-COG on brain area. Stratification based on cognition may help to elucidate the biological underpinnings of cognitive heterogeneity across SZ and BP risk.

Semiconductor clusters: Synthetic precursors for colloidal quantum dots

Semiconductor clusters have been implicated as reaction intermediates between molecular precursors and colloidal quantum dots (CQDs). The success of isolation of semiconductor clusters have enabled detailed investigation of the atomic information of semiconductor clusters. The identification of atomic information has emerged as an important topic because knowledge of the structure-function relationship of intermediate clusters has been helpful to reveal the synthetic mechanism of CQDs. Recently, they have been utilized as the synthetic precursors for CQDs, which was not readily achieved using conventional molecular precursors. This mini review briefly introduces the current understanding of their atomic information such as the composition, structure, and surface. We then discuss advantages, limitations, and the perspective of semiconductor clusters as a precursor for synthesis of CQDs.

A high-resolution spectroscopic search for multiple populations in the 2 Gyr old cluster NGC 1846

ABSTRACT We present detailed C, O, Na, Mg, Si, Ca, Ti, V, Fe, Zr, Ba, and Eu abundance measurements for 20 red giant branch (RGB) stars in the Large Magellanic Cloud (LMC) star cluster NGC 1846 ([Fe/H] = −0.59). This cluster is 1.95 Gyr old and lies just below the supposed lower age limit (2 Gyr) for the presence of multiple populations in massive star clusters. Our measurements are based on high- and low-resolution VLT/FLAMES spectra combined with photometric data from Hubble Space Telescope (HST). Corrections for non-local thermodynamic equilibrium effects are also included for O, Na, Mg, Si, Ca, Fe, and Ba. Our results show that there is no evidence for multiple populations in this cluster based on the lack of any intrinsic star-to-star spread in the abundances of Na and O: We place 95 per cent confidence limits on the intrinsic dispersion for these elements of ≤0.07 and ≤0.09 dex, respectively. However, we do detect a significant spread in the carbon abundances, indicating varying evolutionary mixing occurring on the RGB that increases with luminosity. Overall, the general abundance patterns for NGC 1846 are similar to those seen in previous studies of intermediate-age LMC star clusters and field stars.

ProFeat: Unsupervised image clustering via progressive feature refinement

Unsupervised image clustering is a chicken-and-egg problem that involves representation learning and clustering. To resolve the inter-dependency between them, many approaches that iteratively perform the two tasks have been proposed, but their accuracy is limited due to inaccurate intermediate representations and clusters. To overcome this, this paper proposes ProFeat, a novel iterative approach to unsupervised image clustering based on progressive feature refinement. To learn discriminative features for clustering while avoiding adversarial influence from inaccurate intermediate clusters, ProFeat rigorously divides representation learning and clustering by modeling a neural network for clustering as a composition of an embedding and a clustering function and introducing an auxiliary embedding function. ProFeat progressively refines representations using confident samples from intermediate clusters using an extended contrastive loss. This paper also proposes ensemble-based feature refinement for more robust clustering. Our experiments demonstrate that ProFeat achieves superior results compared to previous methods.