The Neutrino Emissivity of Strange Stars with Ultra Strong Magnetic Field

The effect of a strong magnetic field on the dominant neutrino emissivity in strange stars is investigated. In ultra strong magnetic field, there exists an enhanced neutrino emission because the charged particles are confined to the lowest Landau level. The results show that the neutrino emissivity is proportional to $T^5$ instead of conventional $T^6$, which implies more rapid cooling behavior in magnetars than usual starsComment: 10 pages, 2 figure

A compendium of genetic regulatory effects across pig tissues

The Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.</p

Disease progression patterns and risk factors associated with mortality in deceased patients with COVID‐19 in Hubei Province, China

Background: Detailed descriptions of the patterns of disease progression of deceased coronavirus disease 2019 (COVID-19) patients have not been well explored. Objectives: This study sought to explore disease progression patterns and risk factors associated with mortality of deceased patients with COVID-19. Materials and Methods: Epidemiological, clinical, laboratory, and imaging data (from 15 January to 26 March 2020) of laboratory-confirmed COVID-19 patients were collected retrospectively from two hospitals, Hubei province, China. Disease progression patterns of patients were analyzed based on laboratory data, radiological findings, and Sequential Organ Failure Assessment (SOFA) score. Risk factors associated with death were analyzed. Results: A total of 792 patients were enrolled in this study, of whom 68 died and 724 survived. Complications during hospitalization, such as sepsis, severe acute respiratory distress syndrome, acute cardiac injury, and acute kidney injury, were markedly more frequent in deceased patients than in surviving patients. Deceased patients presented progressive deterioration pattern in laboratory variables, chest computed tomography evaluation, and SOFA score, while surviving patients presented initial deterioration to peak level involvement followed by improvement pattern over time. Days 10 to 14 after illness onset was a critical stage of disease course. Older age, number of preexisting comorbidities ≥2, and SOFA score were independently associated with death for COVID-19. Conclusions: Multiorgan dysfunction was common in deceased COVID-19 patients. Deceased patients presented progressive deterioration pattern, while surviving patients presented a relatively stable pattern during disease progression. Older age, number of preexisting comorbidities ≥2, and SOFA score were independent risk factors for death for COVID-19

Deep Reinforcement Learning for Model Predictive Controller Based on Disturbed Single Rigid Body Model of Biped Robots

This paper modifies the single rigid body (SRB) model, and considers the swinging leg as the disturbances to the centroid acceleration and rotational acceleration of the SRB model. This paper proposes deep reinforcement learning (DRL)-based model predictive control (MPC) to resist the disturbances of the swinging leg. The DRL predicts the swing leg disturbances, and then MPC gives the optimal ground reaction forces according to the predicted disturbances. We use the proximal policy optimization (PPO) algorithm among the DRL methods since it is a very stable and widely applicable algorithm. It is an on-policy algorithm based on the actor–critic framework. The simulation results show that the improved SRB model and the PPO-based MPC method can accurately predict the disturbances of the swinging leg to the SRB model and resist the disturbance, making the locomotion more robust

Deep Reinforcement Learning for Model Predictive Controller Based on Disturbed Single Rigid Body Model of Biped Robots

This paper modifies the single rigid body (SRB) model, and considers the swinging leg as the disturbances to the centroid acceleration and rotational acceleration of the SRB model. This paper proposes deep reinforcement learning (DRL)-based model predictive control (MPC) to resist the disturbances of the swinging leg. The DRL predicts the swing leg disturbances, and then MPC gives the optimal ground reaction forces according to the predicted disturbances. We use the proximal policy optimization (PPO) algorithm among the DRL methods since it is a very stable and widely applicable algorithm. It is an on-policy algorithm based on the actor&ndash;critic framework. The simulation results show that the improved SRB model and the PPO-based MPC method can accurately predict the disturbances of the swinging leg to the SRB model and resist the disturbance, making the locomotion more robust

Involvement of a Cell Wall-Associated Kinase, WAKL4, in Arabidopsis Mineral Responses

The cell wall-associated receptor kinase (WAK) and WAK-like kinase (WAKL) gene family members are good candidates for physical linkers that signal between the cell wall and the cytoplasmic compartment. Previous studies have suggested that while some WAK/WAKL members play a role in bacterial pathogen and heavy-metal aluminum responses, others are involved in cell elongation and plant development. Here, we report a functional role for the WAKL4 gene in Arabidopsis (Arabidopsis thaliana) mineral responses. Confocal microscopic studies localized WAKL4-green fluorescent protein fusion proteins on the cell surfaces suggesting that, like other WAK/WAKL proteins, WAKL4 protein is associated with the cell wall. Histochemical analyses of the WAKL4 promoter fused with the β-glucuronidase reporter gene have shown that WAKL4 expression is induced by Na(+), K(+), Cu(2+), Ni(2+), and Zn(2+). A transgenic line with a T-DNA insertion at 40-bp upstream of the WAKL4 start codon was characterized. While the T-DNA insertion had little effect on the WAKL4 transcript levels under normal growth conditions, it significantly altered the expression patterns of WAKL4 under various conditions of mineral nutrients. Semiquantitative and quantitative reverse transcription-PCR analyses showed that the promoter impairment abolished WAKL4-induced expression by Na(+), K(+), Cu(2+), and Zn(2+), but not by Ni(2+). Whereas the WAKL4 promoter impairment resulted in hypersensitivity to K(+), Na(+), Cu(2+), and Zn(2+), it conferred a better tolerance to toxic levels of the Ni(2+) heavy metal. WAKL4 was required for the up-regulation of zinc transporter genes during zinc deficiency, and the WAKL4 T-DNA insertion resulted in a reduction of Zn(2+) accumulation in shoots. A WAKL4-green fluorescent protein fusion gene driven by either the WAKL4 native promoter or the 35S constitutive promoter complemented the phenotypes. Our results suggest versatile roles for WAKL4 in Arabidopsis mineral nutrition responses