Search Results (423)

In this review, the formation of the Oort Cloud is illuminated from several aspects. One is the history of the subject with an outline of the fundamental discoveries by Öpik, Oort and Hills. It is argued that the basic reason for judging Oort as the real discoverer is that he had access to observational data in the form of original orbits of long period comets. Further landmarks are identified, like the exploration of the role of the Galactic tide in the supply of observable comets by Heisler and Tremaine, the clarification of a synergy between tide and stars as the reason for a continued, efficient supply by Rickman et al., the discovery by Kaib and Quinn that inner core comets become observable due to planetary perturbations, disguised as new comets, and the demonstration of how Oort Cloud formation may work in the realm of the Nice Model by Brasser and Morbidelli. Further discussions refer to the possible role of the Grand Tack model in Oort Cloud formation and recent developments like Pan-STARRS in obtaining better data on very distant comets and Gaia in identifying stellar encounters in the close past and future with ensuing, important modifications of the Oort Cloud. It is finally argued that an important Galactic sculpting has occurred since the primordial Oort Cloud was formed by means of global shake-up events resulting from impulses imparted to the Sun by external perturbers like massive stars or Giant Molecular Clouds, and that this may be the real reason for the survival of an outer halo that reveals the existence of the Oort Cloud through the Oort spike. Full article

This work proposes a fiber-tethered UAV-enabled adaptive aerial passive optical network (AA-PON) framework for rapid extension of optical access and backhaul in hard-to-reach or temporarily disrupted environments. The proposed architecture supports two distinct operating modes: (i) an aerial base station (ABS) mode for wide-area service extension and (ii) a ground-to-air-to-ground (G2A2G) mode for targeted high-speed optical bridging to ground terminal units. Unlike conventional UAV relay approaches, the proposed framework is developed as a network-level optical access/backhaul architecture based on tether-assisted aerial nodes and reconfigurable optical topology formation. In the ABS mode, representative Bus, Ring, and Star topologies are analyzed to evaluate serviceability, outage, deployment latency, and scalability as the number of UAV nodes increases. In the G2A2G mode, a stochastic-geometry-based analysis is used to characterize blockage-limited optical serviceability and infrastructure-density trade-offs. To complement the analytical study, a 2 Gb/s proof-of-concept FSO link between two fiber-tethered UAVs is demonstrated as an initial feasibility validation of the end-to-end optical link. The results show that the proposed AA-PON provides a flexible aerial optical networking framework that combines reconfigurable topology support with localized high-capacity optical access extension. Full article

Nanotechnology continues to advance rapidly, revealing previously unexplored directions in nanoscale communications. Biological and electromagnetic nanonetworks—established communication paradigms at the nanoscale—have shifted interest toward the middle and higher levels of the nanonetworking protocol stack. Motivated by the discovery of Cable Bacteria (CB) and their unique properties, we propose a theoretical model and framework for a new category of nanonetworks: bioelectrical nanonetworks (BioEN). This proposed framework combines the biocompatibility, sustainability and inherent nanodimensions of biological organisms with the networking performance of electromagnetic systems. Large-scale formations (e.g., 10,000 cells spanning nearly 2 cm), together with the electrical characteristics of CB, suggest the feasibility of guided electron-based transport that could complement diffusion-dominated nanonetworks, subject to resistive-capacitive (RC) constraints that remain to be quantified. Furthermore, we present a set of basic network architectures—such as star, ring, and tree—introducing a conceptual bio-multiplexer component, which utilizes CB to form a bioelectrical nanonetwork and illustrate core functionalities primarily at the network layer. Within this theoretical framework, BioEN is positioned as a potential enabler for diverse scientific, environmental, and technological applications, including health and ecosystem biosensing and bioremediation-oriented bioengineering. This work is conceptual and does not experimentally validate a deployed nanonetwork; instead, it establishes the design principles, abstractions, and architectural foundations intended to guide future implementation and experimental verification of bioelectrical nanonetworks. Full article

Classical Be stars are key laboratories for investigating how rapid rotation, pulsations, and mass loss couple to the formation and evolution of circumstellar decretion disks. However, few studies have combined Kepler/K2 photometry with multi-epoch H$\alpha$ monitoring. Here we present four previously unclassified Be-type variable stars observed by K2 (three in Campaign 11 and one in Campaign 15) and followed up with ground-based spectroscopy. We analyzed public PDC light curves and extracted variability frequencies using Lomb–Scargle periodograms and iterative prewhitening with a conservative detection threshold of S/N ≥ 5. Optical spectra obtained at the Observatório Pico dos Dias (Brazil) over a multi-year baseline (2017–2025) include repeated H$\alpha$ observations and blue-region spectra for photospheric characterization. All targets show detectable K2 variability on timescales from hours to days, with frequency spectra ranging from close multi-periodic components producing beating patterns to power dominated by low frequencies. Each star exhibits H$\alpha$ emission at multiple epochs, with long-term changes in line-profile morphology and equivalent width, indicating disk variability on year-long timescales. These results demonstrate that disk evolution can occur without conspicuous photometric outbursts over the time span of space-based observations, highlighting the diagnostic value of combining high-precision space photometry with long-term spectroscopy to characterize multiscale variability in Galactic Be stars. Full article

Riptortus pedestris (Hemiptera, Alydidae) is widely distributed across East Asia, where significant genetic differentiation may occur among geographic populations. To understand the genetic structure, historical dynamics, and formation of geographic distribution patterns in China, we conducted a phylogeographic analysis using three mitochondrial genes (COI, COII, Cytb) from 35 populations. After PCR amplification, we performed genetic diversity analysis, Fst/Nm estimation, phylogenetic reconstruction (ML, BI, NJ), haplotype network, AMOVA, neutrality tests, mismatch distribution, and molecular dating. Results revealed high genetic diversity (Hd > 0.81, π > 0.011), an AT-rich base composition, and faster evolution at the first codon position. Genetic and geographic distances were significantly correlated, with high Fst values indicating strong differentiation, especially between southwestern/southern and other populations. Two main clades were identified: Clade 1 (mainly southern and southwestern China) and Clade 2 (central, northern, northwestern, and northeastern China). A star-like haplotype network and neutrality tests suggested a rapid expansion around 0.019–0.022 Ma (Last Glacial Maximum), and molecular dating estimated the main split at ~0.029 Ma. AMOVA and Gst/Nst confirmed significant phylogeographic structure with most variation among populations. This study provides initial evidence for the genetic differentiation and evolutionary history of R. pedestris in China, demonstrating that its population structure was shaped by climatic changes and geographical isolation, providing key insights into its adaptive evolution and dispersal. Full article

Polycystic ovary syndrome (PCOS) is associated with impaired ovarian steroidogenesis and ovulation, which necessitates the development of effective ovulation inducers for PCOS. The aim of the study was to evaluate the effects of allosteric luteinizing hormone receptor agonist TP03 and human chorionic gonadotropin (hCG) on ovarian steroidogenesis, as well as ovulation in prepubertal female rats with dehydroepiandrosterone(DHEA)-induced PCOS. Taking into account differences in progesterone levels, cohorts with high (PCOS(H)) and low (PCOS(L)) progesterone were formed and treated with Follimag and Cetrotide. After 48 h, TP03 (25 mg/kg) or hCG (25 IU/rat) were injected, and hormone levels, gene expression, and ovarian morphology were assessed. The PCOS(H)-cohort exhibited irregular estrous cycles, ovarian cysts, and increased ovarian mass and estradiol levels, but the number of corpora lutea (CL) was maintained. In the PCOS(L)-cohort, ovarian weight was increased, and Star, Cyp11a1, and Adamts1 gene expression as well as the CL number were decreased. In both cohorts, TP03 and hCG increased progesterone levels and the expression of steroidogenesis (Star, Cyp11a1) and ovulation (Cox2, Adamts1, Egr1) genes, as well as inducing CL formation. Thus, TP03, like hCG, stimulates steroidogenesis and ovulation in PCOS-rats with different progesterone levels, which provides the first evidence of the effectiveness of allosteric LHR agonists as ovulation triggers in PCOS. Full article

In this paper, we discuss the atomic models developed for the non-local thermodynamic equilibrium (LTE) analysis of the spectra of two odd-Z chemical elements, the little-studied potassium and copper, whose nuclei are often thought to form in Cosmos through different astrophysical processes. The K I and Cu I atomic models have been developed and updated over the past decade and applied to determine non-LTE abundances of these elements in the hot and cool dwarfs, giants, and supergiants of different metallicities, from solar to extremely low metallicity. The abundances of potassium and copper in old metal-poor halo stars are of considerable interest because these objects bear the imprints of nucleosynthesis in Type II supernovae and hypernovae in the early Galaxy. The vast majority of the studies of the spectra of these atoms have been based on the assumption of LTE. In some cases, this approach has led to incorrect results, which have sometimes affected our understanding of evolutionary processes in stars and stellar systems. The main objective of this article is to highlight the importance of using the non-LTE stellar abundance data to improve or modify existing theoretical models of cosmic chemical evolution. In particular, significantly different results for the copper abundance in old Galactic stars were obtained compared to LTE data. This finding could inspire specialists working in the field of chemodynamic models to search for realistic pathways for the formation of this element in massive stars. Despite this, since the first non-LTE results on the copper abundance in the oldest Galactic stars, LTE data remained in use for several years. This situation seriously hinders progress in research into some certain aspects of cosmic nucleosynthesis. Full article

Matter in the early Universe was nearly uniform, and galaxies emerged through the gravitational growth of small primordial density fluctuations. Astrophysics has been trying to unveil the complex physical phenomena that have caused the formation and evolution of galaxies throughout the 13-billion-year history of the Universe using the first principles of physics. However, since present-day astrophysical big data contain more than 100 explanatory variables, such a conventional methodology faces limits in dealing with such data. We, instead, elucidate the physics of galaxy evolution by applying manifold learning, one of the latest methods of data science, to a feature space spanned by galaxy luminosities and cosmic time. We discovered a low-dimensional nonlinear structure of data points in this space, referred to as the galaxy manifold. We found that the galaxy evolution in the ultraviolet–optical–near-infrared luminosity space is well described by two parameters, star formation and stellar mass evolution, on the manifold. We also discuss a possible way to connect the manifold coordinates to physical quantities. Full article

Star polymers with dense shell structures exhibit unique advantages in molecule encapsulation. The incorporation of dendronized polymers as arms into star polymers enables the formation of spherical core–shell structures with high-density chain stacking, which is of great significance for enhancing their encapsulation capabilities. Here, we report on the synthesis of a new type of star dendronized polymer consisting of oligoethylene glycol (OEG)-based dendronized polymers as the arms and gold nanoparticles (AuNPs) as the core. Due to the thickness of individual dendronized polymer arms, the morphology of star dendronized polymers was directly visualized by an atomic force microscope (AFM). These star polymers inherit characteristic thermoresponsiveness from the OEG-based dendronized linear polymers, and their thermoresponsive behavior depends mainly on the grafting density of polymer chains on the AuNP cores and the molecular weights of the polymer arms. More importantly, these star dendronized polymers exhibit a tunable encapsulation capacity to guest molecules, which can be modulated through thermally induced aggregation. By virtue of these peculiarities, these thermoresponsive star dendronized polymers with tailorable release properties hold promise as smart nanoboxes for bio-applications, including drug delivery and biosensing. Full article

We present new high-dispersion optical spectra of the planetary nebula NGC 2371 obtained with the Manchester Echelle Spectrometer at the OAN-SPM 2.1 m telescope, complemented with 3D morpho-kinematic modelling using ShapeX. The data reveal that the present-day morphology of NGC 2371 is the outcome of multiple episodic mass-loss events rather than a single outflow. Our best-fitting model simultaneously reproduces the direct images and the Position–Velocity (PV) diagrams, and consists of a barrel-shaped shell with younger polar caps, extended bipolar lobes, and a pair of misaligned low-excitation [N ii] knots interpreted as jet-like ejections. The derived kinematical ages of the main structures, spanning ≃1600 to ≃4400 yr, indicate successive episodes of mass loss with different geometries and timescales. The nearly perpendicular bipolar lobes, the absence of a pronounced waist, and the surface distortions of the large-scale structures cannot be explained solely by standard axisymmetric wind interactions. Instead, our results point to a combination of shaping agents, including a late thermal pulse (born-again scenario) possibly related to the H-deficient [WR]-type nature of the central star, binary-driven interactions, and episodic jet activity. NGC 2371 thus provides a particularly instructive case where multiple shaping agents may operate, and where some of the relevant physical processes remain only marginally explored in current models of PN formation and evolution. Full article

Numerical galaxy formation simulations are sensitive to numerical methods and sub-grid physics models, making code comparison projects essential for quantifying uncertainties. Here, we evaluate gadget4-osaka within the AGORA project framework by conducting a systematic comparison with its predecessor. We perform an isolated disk galaxy and a cosmological zoom-in run of a Milky Way-mass halo, following the multi-step AGORA calibration procedure. By systematically deconstructing the updated stellar feedback model, we demonstrate that mechanical momentum injection is necessary to suppress unphysical gas fragmentation and regulate star formation, yielding agreement with the Kennicutt–Schmidt relation. Meanwhile, stochastic thermal heating is essential for driving a hot metal-enriched gaseous halo, thereby creating a multiphase circumgalactic medium that is absent in the predecessor code. In the cosmological context, we calibrate the simulation to match the stellar mass growth history targeted by the AGORA collaboration. The validated gadget4-osaka simulation has been contributed to the AGORA CosmoRun suite, providing a new data point for understanding the impact of numerical and physical modeling choices on galaxy evolution. Full article

We revisit the extensively debated star-forming main sequence (SFMS)—a tight correlation between the star formation rate and stellar mass in both kiloparsec-resolved and integrated galaxies. We statistically explore the fundamental drivers of star formation at global scales, using a large volume-limited sample of 24,954 local star-forming galaxies to overcome the limitations of previous works. Based on the mid-infrared 12 µm luminosity, stellar mass, and $g-r$ color, we estimate the molecular gas mass for the considered sample. At galaxy-wide scales, we establish global relations between the surface densities of the star formation rate (${\mathrm{\Sigma }}_{\mathrm{SFR}}$), stellar mass (${\mathrm{\Sigma }}_{*}$), and molecular gas mass (${\mathrm{\Sigma }}_{\mathrm{mol}}$). These global density relations are connected with and follow similar trends as the resolved SFMS, the Kennicutt–Schmidt (KS) relation, and the molecular gas main sequence (MGMS). Taking advantage of this large catalog, we show that the scatters in the global KS and MGMS relations are smaller than that of the global relation between ${\mathrm{\Sigma }}_{\mathrm{SFR}}$ and ${\mathrm{\Sigma }}_{*}$, and their Pearson correlation coefficients are higher. More importantly, multivariate regression and partial correlation analyses demonstrate that the apparent ${\mathrm{\Sigma }}_{\mathrm{SFR}}-{\mathrm{\Sigma }}_{*}$ correlation is entirely mediated by ${\mathrm{\Sigma }}_{\mathrm{mol}}$, with its best-fit parameters directly derivable from those of the KS and MGMS relations. Overall, our findings suggest that the correlation between stellar mass and molecular gas, as well as that between molecular gas and star formation, are more direct and fundamental. The star-forming main sequence, thus, appears to be a natural by-product of these two tighter relations. Full article

In Chinese cuisine, seasoning oil enhances the aroma and appearance of dishes. This study examined how processing affects flavor release in multi-ingredient oils. Volatile organic compounds (VOCs), relative odor activity value (ROAV), and variable importance projection (VIP) were used to assess flavor changes. Optimal frying was 160 °C for 15 min with 11% green Sichuan peppercorn, 3% ghost pepper, 6% green onion, 0.1% bay leaf, 0.2% deseeded tsaoko, 0.5% star anise, 0.3% fennel seeds, 1.5% dried Erjingtiao chili, 5% ginger, and 2.5% red Sichuan peppercorn. Gas chromatography–ion mobility spectrometry (GC-IMS) and gas chromatography–mass spectrometry (GC-MS) analyzed heating at 150 °C, 160 °C, and 170 °C. Temperature strongly influenced VOC formation; 160 °C produced the most diverse VOCs, including aldehydes, ketones, terpenes, esters, and alcohols. Multivariate analysis identified 73 key compounds (VIP > 1) between 150 and 160 °C, but only 39 between 160 and 170 °C, indicating that high heat reduces complexity. Compounds such as 2-methylpyrazine and (E)-2-heptenal contributed caramel, nutty, buttery notes, with 2-methoxy-3-(1-methylethyl)-pyrazine as the core aroma. Frying at 160 °C balanced sweet, floral, and roasted aromas, offering guidance for precise seasoning oil flavor control. Full article

Steelmaking involves long, tightly coupled process chains and specialized domain knowledge, making it difficult in practice for a single general-purpose LLM to consistently align engineers’ queries with the correct process stage. This paper presents STAR, an industry-oriented multi-stage process-domain router for steel metallurgy, and provides an integration blueprint that maps routing labels to domain-specific prompting and retrieval scopes in a router-plus-agents architecture. We construct a quality-controlled metallurgical corpus from textbooks, manuals, and papers via OCR and multi-dimensional text-quality scoring. Based on this corpus, we build an LLM-assisted pipeline to synthesize query–domain pairs for eight fine-grained process domains under domain definitions/keywords and format constraints, and index all queries in a shared embedding space with FAISS. We design a three-stage router: (1) a lightweight filter using chit-chat rules and a nearest-neighbor distance threshold to separate steel-related queries from general ones, (2) a kNN label-voting router whose confidence is derived from the Top-k neighbor label concentration, and (3) an LLM-based refinement step for low-confidence cases with safe fallback. Experiments on 3136 steel-domain queries and approximately 2000 general queries show that STAR achieves 0.921 Top-1 accuracy and 0.899 macro-F1 on 8-way fine-grained steel-domain routing, and achieves a steel-query recall of 0.999 for steel-versus-general filtering (queries routed to general_llm in deployment). In this work, we primarily evaluate routing quality and efficiency; end-to-end answer quality evaluation of downstream agents is left for future work. Full article

This study investigated how gifted and regular high school students employ different cognitive strategies and integrate information during scientific problem solving, using eye-tracking techniques. Eighteen multiple-choice items were selected from the Investigating Scientific Thinking and Reasoning (iSTAR) assessment developed at The Ohio State University, including nine text-only questions (tMCQs) and nine picture-embedded questions (pMCQs). The items were chosen to ensure clear spatial separation among text, image, and answer areas, allowing reliable region-based eye-movement analysis. Eye-tracking data were analyzed using two indices: fixation time ratio (FTR), reflecting relative attention allocation, and saccade count ratio (SCR), capturing cross-region information integration. The results revealed clear group differences. Gifted students devoted a larger proportion of attention to pictorial information (0.38 vs. 0.32) and showed more frequent transitions between picture and answer regions (0.15 vs. 0.12), indicating more integrative processing and mental model construction. In contrast, regular students spent more time focusing on textual regions and exhibited higher within-text saccade activity, consistent with a direct translation strategy. Furthermore, SCR-based machine learning classification using a Random Forest model demonstrated meaningful discriminative capability between the two groups, particularly for picture-embedded questions, achieving an accuracy of 77.5%. Overall, the findings provide empirical evidence that question format influences students’ cognitive strategies during scientific reasoning. Methodologically, this study combines a validated reasoning assessment, a carefully defined ROI-based eye-tracking design, and interpretable behavioral indicators, offering practical implications for differentiated science instruction. Full article