Device-to-Device Assisted Video Transmission

To increase spectrum efficiency, researchers envi- sion a device-to-device (D2D) communication system in which a closely located mobile device pair may share the same spectrum with a cellular user. By opportunistically choosing the frequency, the D2D pair may increase the spectrum efficiency in terms of data rate per Hertz, at the price of additional interference to that cellular user. In previous models, users either stop cellular transmission and switch to D2D transmission or vice versa. However, if the cell is fully loaded, a D2D pair will not be able to switch back to the conventional mode because no extra resource is available. In this paper, we propose a D2D assisted model, where a D2D link is enabled to assist transmission, while keeping the conventional cellular transmission. In this way, the D2D link can be turned on and off according to the link quality. We also propose a PHY-layer study for the transmission scheme in such a way that the system throughput and the video reception quality is always improved compared to a conventional link

Review of dynamic modelling, system identification and control scheme in solvent-based post-combustion carbon capture process

Solvent-based post-combustion carbon capture (PCC) process is widely viewed as the most viable option for reducing CO 2 emission. This technology has been deployed globally and many researches have been conducted in this area. In this paper, current status of dynamic modelling, system identification and control scheme of solvent-based PCC process is reviewed. Different research directions of these areas are discussed to conclude the existing challenges. Based on this, this paper is also trying to provide potential solutions as possible pathways for flexible and economical operation

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Causal associations of COVID‐19 on neurosurgical diseases risk: a Mendelian randomization study

Abstract Many researchers have explored the potential association between one neurosurgical disease and coronavirus disease 2019 (COVID-19), but few systematically analyzed the association and causality between COVID-19 and various neurosurgical diseases. A Mendelian randomization analysis was conducted to evaluate the causal association between COVID-19 (including critically ill COVID‐19, hospitalized COVID‐19, and respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection) and 30 neurosurgical diseases within European populations. The consequences of inverse variance weighted models suggest that genetic susceptibility of critically ill COVID-19 may increase the risk of cerebral infarction (odds ratio [OR] = 1.02; p‐value = 0.006), genetic susceptibility of SARS-CoV-2 infection may increase the risk of stroke (OR = 1.02; p‐value = 0.047), and conversely, genetic susceptibility of hospitalized COVID-19 may reduce the risk of pituitary adenoma and craniopharyngioma (OR = 0.90; p‐value = 0.032). In addition, evidences revealed potential associations between genetic susceptibility of COVID-19 and spinal stenosis (OR = 1.03; p‐value = 0.028), diffuse brain injury (OR = 1.21; p‐value = 0.040) and focal brain injury (OR = 1.12; p‐value = 0.040). By testing for heterogeneity and pleiotropy, the above causal conclusions are robust. In summary, our analysis shows that COVID-19 has an independent and powerful causal influence on multiple neurosurgical disorders

Systematic analysis based on the cuproptosis-related genes identifies ferredoxin 1 as an immune regulator and therapeutic target for glioblastoma

Abstract Glioblastoma multiforme (GBM) is recognized as the prevailing malignant and aggressive primary brain tumor, characterized by an exceedingly unfavorable prognosis. Cuproptosis, a recently identified form of programmed cell death, exhibits a strong association with cancer progression, therapeutic response, and prognostic outcomes. However, the specific impact of cuproptosis on GBM remains uncertain. To address this knowledge gap, we obtained transcriptional and clinical data pertaining to GBM tissues and their corresponding normal samples from various datasets, including TCGA, CGGA, GEO, and GTEx. R software was utilized for the analysis of various statistical techniques, including survival analysis, cluster analysis, Cox regression, Lasso regression, gene enrichment analysis, drug sensitivity analysis, and immune microenvironment analysis. Multiple assays were conducted to investigate the expression of genes related to cuproptosis and their impact on the proliferation, invasion, and migration of glioblastoma multiforme (GBM) cells. The datasets were obtained and prognostic risk score models were constructed and validated using differentially expressed genes (DEGs) associated with cuproptosis. To enhance the practicality of these models, a nomogram was developed.Patients with glioblastoma multiforme (GBM) who were classified as high risk exhibited a more unfavorable prognosis and shorter overall survival compared to those in the low risk group. Additionally, we specifically chose FDX1 from the differentially expressed genes (DEGs) within the high risk group to assess its expression, prognostic value, biological functionality, drug responsiveness, and immune cell infiltration. The findings demonstrated that FDX1 was significantly upregulated and associated with a poorer prognosis in GBM. Furthermore, its elevated expression appeared to be linked to various metabolic processes and the susceptibility to chemotherapy drugs. Moreover, FDX1 was found to be involved in immune cell infiltration and exhibited correlations with multiple immunosuppressive genes, including TGFBR1 and PDCD1LG2. The aforementioned studies offer substantial assistance in informing the chemotherapy and immunotherapy approaches for GBM. In summary, these findings contribute to a deeper comprehension of cuproptosis and offer novel perspectives on the involvement of cuproptosis-related genes in GBM, thereby presenting a promising therapeutic strategy for GBM patients

Additional file 1 of Causal associations of COVID‐19 on neurosurgical diseases risk: a Mendelian randomization study

Additional file 1: Table S1. Single-nucleotide polymorphisms associated with COVID-19 (P < 1 × 10−5). √ is confounding factor, × is non-confounding factor