Degeneracy and Discreteness in Cosmological Model Fitting

We explore the degeneracy and discreteness problems in the standard cosmological model (\Lambda CDM). We use the Observational Hubble Data (OHD) and the type Ia supernova (SNe Ia) data to study this issue. In order to describe the discreteness in fitting of data, we define a factor G to test the influence from each single data point and analyze the goodness of G. Our results indicate that a higher absolute value of G shows a better capability of distinguishing models, which means the parameters are restricted into smaller confidence intervals with a larger figure of merit evaluation. Consequently, we claim that the factor G is an effective way in model differentiation when using different models to fit the observational data.Comment: 12 pages, 4 figures, 1 table, accepted by RA

Dynamic Network Representation Learning Method Based on Improved GRU Network

As social networks have been rapidly growing, traditional network representation learning methods are struggling to accurately characterize their dynamic changes, and to output effective node classification and link prediction. To address this problem, this paper proposes IproGRU, a dynamic network representation learning method based on an improved Gated Recurrent Unit (GRU) network to improve the dynamic network representation. First, the method quickly generates embedding for an influenced node by sampling and aggregating features of its neighboring nodes when the network changes. Second, it updates the embedding of the influenced node on time series by the improved GRU network to fully adapt to the changes of the dynamic network. Experimental results on node classification and link prediction for three datasets of dynamic networks show that the proposed method improves the accuracy by 5–10 % on average from those of the traditional Node2vec and GraphSAGE methods and has a slight advantage over Graph Convolutional Networks (GCNs). The results demonstrate that our method is effective for dynamic network representation.

A Gravitational Wave Detector for Post Merger Neutron Stars: Beyond the Quantum Loss Limit of Michelson Fabry Perot Interferometer

Advanced gravitational-wave detectors that have made groundbreaking discoveries are Michelson interferometers with resonating optical cavities as their arms. As light travels at finite speed, these cavities are optimal for enhancing signals at frequencies below their bandwidth frequency. A small amount of optical loss will, however, significantly impact the high-frequency signals which are not optimally amplified. We find an elegant interferometer configuration with an "L-resonator" as the core, significantly surpassing the loss limited sensitivity of dual recycled Fabry Perot Michelson interferometers at high frequencies. Following this concept, we provide a broadband design of a 25 km detector with outstanding sensitivity between 2-4 kHz. We have performed Monte-Carlo population studies of binary neutron star mergers, given the most recent merger rate from the GWTC-3 catalog and several representative neutron star equations of state. We find that the new interferometer configuration significantly outperforms other third-generation detectors by a factor of 3 to 7 in the signal-to-noise ratio of the post-merger signal. Assuming a detection threshold with signal-to-noise ratio >5 and for the cases we have explored, the new design is the only detector that confidently achieves a detection rate larger than one per year, with the rate being 1 to 30 events per year.Comment: 12 pages, 9 figure

TLE3 represses colorectal cancer proliferation by inhibiting MAPK and AKT signaling pathways

Primer Sequences used for RT-qPCR (5’ to 3’). (DOCX 13 kb

The impact of Sarcocystis infection on lamb flavor metabolites and its underlying molecular mechanisms

IntroductionMeat flavor is a critical factor for consumers to evaluate meat quality and a key determinant of its market value. Sarcocystis spp. are widely distributed parasitic protozoa that infect livestock, leading to reduced meat quality, fur, and fiber, and causing significant economic losses. However, most studies focus on the pathogenic mechanisms and epidemiological characteristics of Sarcocystis, with limited research on its specific impact on meat quality and flavor, particularly the underlying molecular regulatory mechanisms.MethodsThis study investigated the effects of Sarcocystis infection on meat flavor and its molecular mechanisms in Tibetan sheep using flavor metabolite analysis and transcriptomic approaches. Tibetan sheep raised under uniform conditions were divided into four groups based on infection severity: normal, low-infection, moderate-infection, and high-infection. Leg muscle samples were collected for flavor metabolite analysis and transcriptome sequencing. Differentially expressed metabolites (DEMs) and differentially expressed genes (DEGs) were identified, and KEGG pathway enrichment analysis was performed to explore how Sarcocystis infection regulates gene expression, affecting lipid, amino acid, and energy metabolism, ultimately altering the production and accumulation of flavor metabolites.ResultsThe results showed that Sarcocystis infection significantly altered the composition of flavor metabolites in Tibetan sheep meat as infection severity increased. Phenolic and acidic metabolites were markedly upregulated, intensifying bitterness and sourness, while ketone and lactone metabolites were downregulated, reducing fatty and creamy aromas. Transcriptomic analysis identified 574 DEGs, including upregulated genes such as MAPK12, COX6A2, and RXRA, which are involved in lipid metabolism, fatty acid oxidation, and thermogenesis, and downregulated genes such as COX2, COX3, and ADIPOQ, which are associated with mitochondrial function and energy metabolism. These gene expression changes disrupted lipid and amino acid metabolism, leading to imbalances in the synthesis and accumulation of flavor compounds.DiscussionThis study systematically revealed the significant effects of Sarcocystis infection on the meat flavor of Tibetan sheep and its underlying molecular mechanisms. The findings provide new insights into the metabolic regulation induced by parasitic infection and offer a theoretical basis for mitigating the adverse effects of Sarcocystis infection on meat quality

Toward observing neutron star collapse with gravitational wave detectors

Gravitational waves from binary neutron star inspirals have been detected along with the electromagnetic transients coming from the aftermath of the merger in GW170817. However, much is still unknown about the postmerger dynamics that connects these two sets of observables. This includes if, and when, the postmerger remnant star collapses to a black hole, and what are the necessary conditions to power a short gamma-ray burst and other observed electromagnetic counterparts. Observing the collapse of the postmerger neutron star would shed light on these questions, constraining models for the short gamma-ray burst engine and the hot neutron star equation of state. In this work, we explore the scope of using gravitational wave detectors to measure the timing of the collapse either indirectly, by establishing the shutoff of the postmerger gravitational emission, or—more challengingly—directly, by detecting the collapse signal. For the indirect approach, we consider a kilohertz high-frequency detector design that utilizes a previously studied coupled arm cavity and signal recycling cavity resonance. This design would give a signal-to-noise ratio of 0.5–8.6 (depending on the variation of waveform parameters) for a collapse gravitational wave signal occurring at 10 ms postmerger of a binary at 50 Mpc and with total mass 2.7  ⊙. This detector design is limited by quantum shot noise and the signal-to-noise ratio largely depends on the detector power, which is adopted as 4 MW in this work. For the direct approach, we propose a narrow band detector design, utilizing the sensitivity around the frequency of the arm cavity free spectral range. To attain the maximal achievable quantum sensitivity, which is fundamentally limited by optical loss, we suggest the application of an optomechanical filter cavity that converts the signal recycling cavity into a signal amplifier. The proposed detector achieves a signal-to-noise ratio of 0.3–1.9, independent of the collapse time. This detector is limited by both the fundamental classical and quantum noise with the arm cavity power chosen as 10 MW