Insights into neutron star equation of state by machine learning

Due to its powerful capability and high efficiency in big data analysis, machine learning has been applied in various fields. We construct a neural network platform to constrain the behaviors of the equation of state of nuclear matter with respect to the properties of nuclear matter at saturation density and the properties of neutron stars. It is found that the neural network is able to give reasonable predictions of parameter space and provide new hints into the constraints of hadron interactions. As a specific example, we take the relativistic mean field approximation in a widely accepted Walecka-type model to illustrate the feasibility and efficiency of the platform. The results show that the neural network can indeed estimate the parameters of the model at a certain precision such that both the properties of nuclear matter around saturation density and global properties of neutron stars can be saturated. The optimization of the present modularly designed neural network and extension to other effective models are straightforward.Comment: 12 pages, 5 figures. Comments are welcom

Influence of Renewable Energy Sources on Day Ahead Optimal Power Flow Based on Meteorological Data Forecast Using Machine Learning: A case study of Johor Province

This article investigates a day ahead optimal power flow considering the intermittent nature of renewable energy sources that involved with weather conditions. The article integrates the machine learning into power system operation to predict precisely day ahead meteorological data (wind speed, temperature and solar irradiance) that influence directly on the calculations of generated power of wind turbines and solar photovoltaic generators. Consequently, the power generation schedulers can make appropriate decisions for the next 24 hours. The proposed research uses conventional IEEE -30-bus as a test system running in Johor province that selected as a test location. algorithm designed in Matlab is utilized to accomplish the day ahead optimal power flow. The obtained results show that the true and predicted values of meteorological data are similar significantly and thus, these predicted values demonstrate the feasibility of the presented prediction in performing the day ahead optimal power flow. Economically, the obtained results reveal that the predicted fuel cost considering wind turbines and solar photovoltaic generators is reduced to 645.34 USD/h as compared to 802.28 USD/h of the fuel cost without considering renewable energy sources. Environmentally, CO2 emission is reduced to 340.9 kg/h as compared to 419.37 kg/h of the conventional system. To validate the competency of the whale optimization, the OPF for the conventional system is investigated by other 2 metaheuristic optimization techniques to attain statistical metrics for comparative analysis

Study of the Mechanical and Morphology Properties of Recycled HDPE Composite Using Rice Husk Filler

WPCs are being used in a large number of applications in the automotive, construction, electronic, and aerospace industries. There are an increasing number of research studies and developments in WPC technology involving rice husk as fillers. This study investigated the effects of different compositions of rice husk (RH) filler on the mechanical and morphological properties of recycled HDPE (rHDPE) composite. The composites were prepared with five different loading contents of RH fibers (0, 10, 20, 30, and 40 wt%) using the twin screw extrusion method. Maleic acid polyethylene (MAPE) was added as a coupling agent. Results showed that tensile and flexural properties improved with increasing RH loading. However, the impact strength of the composites decreased as the RH loading increased. SEM micrographs revealed good interfacial bonding between the fiber and polymer matrix

Astrocyte metabolism and signaling pathways in the CNS

Astrocytes comprise half of the cells in the central nervous system and play a critical role in maintaining metabolic homeostasis. Metabolic dysfunction in astrocytes has been indicated as the primary cause of neurological diseases, such as depression, Alzheimer’s disease, and epilepsy. Although the metabolic functionalities of astrocytes are well known, their relationship to neurological disorders is poorly understood. The ways in which astrocytes regulate the metabolism of glucose, amino acids, and lipids have all been implicated in neurological diseases. Metabolism in astrocytes has also exhibited a significant influence on neuron functionality and the brain’s neuro-network. In this review, we focused on metabolic processes present in astrocytes, most notably the glucose metabolic pathway, the fatty acid metabolic pathway, and the amino-acid metabolic pathway. For glucose metabolism, we focused on the glycolysis pathway, pentose-phosphate pathway, and oxidative phosphorylation pathway. In fatty acid metabolism, we followed fatty acid oxidation, ketone body metabolism, and sphingolipid metabolism. For amino acid metabolism, we summarized neurotransmitter metabolism and the serine and kynurenine metabolic pathways. This review will provide an overview of functional changes in astrocyte metabolism and provide an overall perspective of current treatment and therapy for neurological disorders

Multi-Host Model-Based Identification of \u3ci\u3eArmillifer agkistrodontis\u3c/i\u3e (Pentastomida), a New Zoonotic Parasite from China

Background: Pentastomiasis is a rare parasitic infection of humans. Pentastomids are dioecious obligate parasites requiring multiple hosts to complete their life cycle. Despite their worm-like appearance, they are commonly placed into a separate sub-class of the subphylum Crustacea, phylum Arthropoda. However, their systematic position is not uncontested and historically, they have been considered as a separate phylum. Methodology/Principal Findings: An appraisal of Armillifer agkistrodontis was performed in terms of morphology and genetic identification after its lifecycle had been established in a multi-host model, that is, mice and rats as intermediate hosts, and snakes (Agkistrodon acutus and Python molurus) as definitive hosts. Different stages of the parasite, including eggs, larvae and adults, were isolated and examined morphologically using light and electron microscopes. Phylogenetic and cluster analysis were also undertaken, focusing on the 18S rRNA and the Cox1 gene. The time for lifecycle completion was about 14 months, including 4 months for the development of eggs to infectious larvae in the intermediate host and 10 months for infectious larvae to mature in the final host. The main morphological difference between A. armillatus and Linguatula serrata is the number of abdominal annuli. Based on the 18S rRNA sequence, the shortest hereditary distance was found between A. agkistrodontis and Raillietiella spp. The highest degree of homology in the Cox 1 nucleic acid sequences and predicted amino acid sequences was found between A. agkistrodontis and A. armillatus. Conclusion: This is the first time that a multi-host model of the entire lifecycle of A. agkistrodontis has been established. Morphologic and genetic analyses supported the notion that pentastomids should be placed into the phylum Arthropoda

Multi-host Model-Based Identification of Armillifer agkistrodontis (Pentastomida), a New Zoonotic Parasite from China

Little information is currently available on the lifecycle and morphology of pentastomids, a new zoonotic parasite in China. The lifecycle of Armillifer agkistrodontis was established in multiple hosts, i.e., an intermediate host and a definitive host, and the parasite examined in terms of morphology and genetic relationship with other species. The time required for the completion of an entire lifecycle was about 14 months. The main morphological difference between A. armillatus and L. serrata is the number of abdominal annuli. The genetic data supported the notion that pentastomids belong to the phylum Arthropoda. Based on the 18S rRNA sequence, the shortest hereditary distance was found between A. agkistrodontis and Raillietiella spp. The highest similarity in the Cox 1 nucleic acid sequences was found between A. agkistrodontis and A. armillatus. The established multi-host model provides a possible approach to confirm suspected infections and offers an opportunity to further study this parasite

ADAR2-dependent RNA editing of GluR2 is involved in thiamine deficiency-induced alteration of calcium dynamics

BACKGROUND: Thiamine (vitamin B1) deficiency (TD) causes mild impairment of oxidative metabolism and region-selective neuronal loss in the central nervous system (CNS). TD in animals has been used to model aging-associated neurodegeneration in the brain. The mechanisms of TD-induced neuron death are complex, and it is likely multiple mechanisms interplay and contribute to the action of TD. In this study, we demonstrated that TD significantly increased intracellular calcium concentrations [Ca2+]i in cultured cortical neurons. RESULTS: TD drastically potentiated AMPA-triggered calcium influx and inhibited pre-mRNA editing of GluR2, a Ca2+-permeable subtype of AMPA receptors. The Ca2+ permeability of GluR2 is regulated by RNA editing at the Q/R site. Edited GluR2 (R) subunits form Ca2+-impermeable channels, whereas unedited GluR2 (Q) channels are permeable to Ca2+ flow. TD inhibited Q/R editing of GluR2 and increased the ratio of unedited GluR2. The Q/R editing of GluR2 is mediated by adenosine deaminase acting on RNA 2 (ADAR2). TD selectively decreased ADAR2 expression and its self-editing ability without affecting ADAR1 in cultured neurons and in the brain tissue. Over-expression of ADAR2 reduced AMPA-mediated rise of [Ca2+]i and protected cortical neurons against TD-induced cytotoxicity, whereas down-regulation of ADAR2 increased AMPA-elicited Ca2+ influx and exacerbated TD-induced death of cortical neurons. CONCLUSIONS: Our findings suggest that TD-induced neuronal damage may be mediated by the modulation of ADAR2-dependent RNA Editing of GluR2

Study on the relationship of acute ketosis intoxication and type 2 diabetes mellitus

AbstractObjectiveTo study the change of serum C-reactive protein (CRP) levels and its correlation with ketosis in type 2 diabetes mellitus patients with acute ketosis intoxication.MethodsA retrospective analysis was conducted for the patients with type 2 diabetes mellitus from August 2015 to January 2016. The patients combined with ketosis were included into diabetic ketosis group and the patients without ketosis were included into negative control group. The clinical data were collected from two groups including general data, blood pressure, liver function and the levels of blood fat, glycosylated hemoglobin, blood ketone, β-hydroxybutyric acid and CRP. The discrepancy of clinical data between two groups was analyzed.ResultsThe levels of glycosylated hemoglobin [(11.6 ± 2.1)% vs. (8.3 ± 1.9)%], blood ketone [0.65 (0.3, 1.75) vs. 0.1 (0.1, 0.2) mmol/L], β-hydroxybutyric acid [0.595 (0.303, 1.775) vs. 0.08 (0.06, 0.15) mmol/L] and CRP [0.595 (0.303, 1.775) vs. 0.08 (0.06, 0.15) mmol/L] were significant higher than those of negative control group, while the levels of blood pressure, blood fat and aminopherase had no significant difference. The serum CRP levels showed positive correlation with blood ketone and β-hydroxybutyric acid (r = 0.490 and r = 0.478, respectively).ConclusionsPoor blood glucose control for a long time and strengthening inflammatory response are correlated with the status of acute ketosis in type 2 diabetes mellitus patients. The CRP levels in ketosis patients were significantly elevated and could be used to evaluate the degree of ketosis