Practice Study on Operation Evaluation and Limitation for Merchant Ships in Polar Water

All environmental hazards impact safety for polar ships, especially polar merchant ship with light ice-class. In order to provide a systematic guidance to deal with any situation during polar operation, International Maritime Organization (IMO) raised mandatory requirements of “Polar Water Operation Manual”(PWOM) in Polar Code. This paper focuses on how to determinate operational evaluation and limitation for the PWOM, which is an important measure to avoid polar ships exceeding operational capability. Features of polar navigation are summarized based on the former polar navigation experience, and typical risk model is set up to describe the process of operation evaluation. The operational limitation is analyzed to indicate the actual capability and limitation as the ship encounters unexpected incident in polar waters. In conclusion, the operation procedure is studied to give a detailed technical proposals for the whole polar operation, which is the main component of PWOM. The outcome may provide helpful to arctic shipping of merchant ships

Personalized Federated Deep Reinforcement Learning-based Trajectory Optimization for Multi-UAV Assisted Edge Computing

In the era of 5G mobile communication, there has been a significant surge in research focused on unmanned aerial vehicles (UAVs) and mobile edge computing technology. UAVs can serve as intelligent servers in edge computing environments, optimizing their flight trajectories to maximize communication system throughput. Deep reinforcement learning (DRL)-based trajectory optimization algorithms may suffer from poor training performance due to intricate terrain features and inadequate training data. To overcome this limitation, some studies have proposed leveraging federated learning (FL) to mitigate the data isolation problem and expedite convergence. Nevertheless, the efficacy of global FL models can be negatively impacted by the high heterogeneity of local data, which could potentially impede the training process and even compromise the performance of local agents. This work proposes a novel solution to address these challenges, namely personalized federated deep reinforcement learning (PF-DRL), for multi-UAV trajectory optimization. PF-DRL aims to develop individualized models for each agent to address the data scarcity issue and mitigate the negative impact of data heterogeneity. Simulation results demonstrate that the proposed algorithm achieves superior training performance with faster convergence rates, and improves service quality compared to other DRL-based approaches

Altered expression of circadian clock gene, mPer1, in mouse brain and kidney under morphine dependence and withdrawal

Every physiological function in the human body exhibits some form of circadian rhythmicity. Under pathological conditions, however, circadian rhythmicity may be dusrupted. Patients infected with HIV or addicted to drugs of abuse often suffer from sleep disorders and altered circadian rhythms. Early studies in Drosophila suggested that drug seeking behavior might be related to the expression of certain circadian clock genes. Our previous research showed that conditioned place preference with morphine treatment was altered in mice lacking the Period-1 (mPer1) circadian clock gene. Thus, we sought to investigate whether morphine treatment could alter the expression of mPer1, especially in brain regions outside the SCN and in peripheral tissues. Our results using Western blot analysis showed that the mPER1 immunoreactivity exhibited a strong circadian rhythm in the brains of the control (Con), morphine-dependent (MD), and morphine-withdrawal (MW) mice. However, the phase of the circadian rhythm of mPER1 expression in the brains of MD mice significantly differed from that of the Con mice (p < 0.05). In contrast to mPER1 expression in the brain, the circadian rhythm of mPER1 immunoreactivity in the kidneys was abolished after morphine administration, whereas the Con mice maintained robust circadian rhythmicity of mPER1 in the kidney. Therefore, the effect of morphine on the circadian clock gene mPer1 may vary among different organs, resulting in desynchronization of circadian function between the SCN and peripheral organs. Originally published Journal of Circadian Rhythms, Vol. 4, No. 9, Aug 2006

A Candidate for the Least-massive Black Hole in the First 1.1 Billion Years of the Universe

We report a candidate of a low-luminosity active galactic nucleus (AGN) at z = 5 that was selected from the first near-infrared images of the JWST CEERS project. This source, named CEERS-AGN-z5-1 at absolute 1450 \uc5 magnitude M 1450 = −19.5 \ub1 0.3, was found via a visual selection of compact sources from a catalog of Lyman break galaxies at z &gt; 4, taking advantage of the superb spatial resolution of the JWST/NIRCam images. The 20 photometric data available from CFHT, Hubble Space Telescope, Spitzer, and JWST suggest that the continuum shape of this source is reminiscent of that for an unobscured AGN, and there is a clear color excess in the filters where the redshifted Hβ+[O iii] and Hα are covered. The estimated line luminosity is L Hβ+[O III] = 1043.0 erg s−1 and L Hα = 1042.9 erg s−1 with the corresponding rest-frame equivalent width EWHβ+[O III] = 1100 \uc5 and EWHα = 1600 \uc5, respectively. Our spectral energy distribution fitting analysis favors the scenario that this object is either a strong broad-line emitter or even a super-Eddington accreting black hole (BH), although a possibility of an extremely young galaxy with moderate dust attenuation is not completely ruled out. The bolometric luminosity, L bol = 2.5 \ub1 0.3 7 1044 erg s−1, is consistent with those of z &lt; 0.35 broad-line AGNs with M BH ∼ 106 M ⊙ accreting at the Eddington limit. This new AGN population in the first 1.1 billion years of the universe may close the gap between the observed BH mass range at high redshift and that of BH seeds. Spectroscopic confirmation is awaited to secure the redshift and its AGN nature

New Measles Virus Genotype Associated with Outbreak, China

Better understanding of transmission patterns will enhance control and elimination programs

Single Endemic Genotype of Measles Virus Continuously Circulating in China for at Least 16 Years

The incidence of measles in China from 1991 to 2008 was reviewed, and the nucleotide sequences from 1507 measles viruses (MeV) isolated during 1993 to 2008 were phylogenetically analyzed. The results showed that measles epidemics peaked approximately every 3 to 5 years with the range of measles cases detected between 56,850 and 140,048 per year. The Chinese MeV strains represented three genotypes; 1501 H1, 1 H2 and 5 A. Genotype H1 was the predominant genotype throughout China continuously circulating for at least 16 years. Genotype H1 sequences could be divided into two distinct clusters, H1a and H1b. A 4.2% average nucleotide divergence was found between the H1a and H1b clusters, and the nucleotide sequence and predicted amino acid homologies of H1a viruses were 92.3%–100% and 84.7%–100%, H1b were 97.1%–100% and 95.3%–100%, respectively. Viruses from both clusters were distributed throughout China with no apparent geographic restriction and multiple co-circulating lineages were present in many provinces. Cluster H1a and H1b viruses were co-circulating during 1993 to 2005, while no H1b viruses were detected after 2005 and the transmission of that cluster has presumably been interrupted. Analysis of the nucleotide and predicted amino acid changes in the N proteins of H1a and H1b viruses showed no evidence of selective pressure. This study investigated the genotype and cluster distribution of MeV in China over a 16-year period to establish a genetic baseline before MeV elimination in Western Pacific Region (WPR). Continuous and extensive MeV surveillance and the ability to quickly identify imported cases of measles will become more critical as measles elimination goals are achieved in China in the near future. This is the first report that a single endemic genotype of measles virus has been found to be continuously circulating in one country for at least 16 years

Reduced expression of lamin A/C correlates with poor histological differentiation and prognosis in primary gastric carcinoma

<p>Abstract</p> <p>Background</p> <p>Lamin A/C is very important in DNA replication, RNA dependent transcription and nuclear stabilization. Reduced or absent lamin A/C expression has been found to be a common feature of a variety of different cancers. To investigate the role of lamin A/C in gastric carcinoma (GC) pathogenesis, we analyzed the correlations between the lamin A/C expression level and clinicopathological factors and studied its prognostic role in primary GC.</p> <p>Methods</p> <p>The expression of lamin A/C at mRNA level was detected by the reverse transcription-polymerase chain reaction (RT-PCR) and real time RT-PCR, and western blot was used to examine the protein expression. Lamin A/C expression and its prognostic significance were investigated by performing immunohistochemical analysis on a total of 126 GC clinical tissue samples.</p> <p>Results</p> <p>Both lamin A/C mRNA and protein expression were downregulated in the majority of tumours compared with corresponding normal gastric tissues (<it>p </it>= 0.011 and <it>p </it>= 0.036, respectively). Real time RT-PCR further validated that downregulation of lamin A/C is associated with poor histological differentiation (r = 0.438, <it>p </it>= 0.025). The immunohistochemical staining showed an evident decrease of lamin A/C expression in 55.6% (70/126) GC cases. Importantly, the negative lamin A/C expression correlated strongly with histological classification (r = 0.361, <it>p </it>= 0.034). Survival analysis revealed that patients with lamin A/C downregulation have a poorer prognosis (<it>p </it>= 0.034). In addition, lamin A/C expression was found to be an independent prognostic factor by multivariate analysis.</p> <p>Conclusion</p> <p>Data of this study suggest that lamin A/C is involved in the pathogenesis of GC, and it may serve as a valuable biomarker for assessing the prognosis for primary GC.</p

Optimization of Psychological Characteristics and Education Management Path of Poor College Students in Colleges and Universities Based on Improved PCA

Aiming at the mental health problems of poor college students, this study proposes an expression recognition method based on the optimization of PCA algorithm and applies it to the mental health test framework. By comparing the differences between poor college students and norms, and using multiple linear regression and typical correlation analysis to explore the impact of educational management paths. The study also addressed the effect of different types of colleges and universities on the level of management of academic support for poor students, and found that 985 colleges and universities significantly outperformed the norm in this area, i.e. P > |t| = 0.031. This provides valuable insights into improving educational and psychological support for poor college students