Does Unruh radiation accelerate the universe? A novel approach to the cosmic acceleration

We present a novel mechanism for the present acceleration of the universe. We find that the temperature of the Unruh radiation perceived by the brane is not equal to the inherent temperature (Hawking temperature at the apparent horizon) of the brane universe in the frame of Dvali-Gabadadze-Porrati (DGP) braneworld model. The Unruh radiation perceived by a dust dominated brane is always warmer than the brane measured by the geometric temperature, which naturally induces an energy flow between bulk and brane based on the most sound thermodynamics principles. Through a thorough investigation to the microscopic mechanism of interaction between bulk Unruh radiation and brane matter, we put forward that an energy influx from bulk Unruh radiation to the dust matter on the brane accelerates the universe.Comment: 28 pages, 4 figs, to appear in NPB; This is a joint paper of hep-th/0607166 and astro-ph/0607531, which will be withdraw

Probing the nature of cosmic acceleration

The cosmic acceleration is one of the most significant cosmological discoveries over the last century. The two categories of explanation are exotic component (dark energy) and modified gravity. We constrain the two types of model by a joint analysis with perturbation growth and direct $H(z)$ data. Though the minimal $\chi^2$ of the $\Lambda$CDM is almost the same as that of DGP, in the sense of consistency we find that the dark energy ($\Lambda$CDM) model is more favored through a detailed comparison with the corresponding parameters fitted by expansion data.Comment: 10 pages, 6 figures, typo correcte

Public perspective on renewable and other energy resources: Evidence from social media big data and sentiment analysis

To address global climate change, many countries are reducing CO2 emissions and replacing conventional energy resources with alternative ones. When developing national energy plans, it is essential to investigate public perspectives on the relationship between renewable and other energy resources. This study employs sentiment and correlation analyses of social media data to assess public perspectives on the complex relationships between renewable and other energy resources. The results show that renewable energy and nuclear energy have a complementary relationship in terms of positive emotions, but a substitute relationship in terms of negative emotions. These findings can inform regional and national energy plans and policies for renewable and nuclear energy. Additionally, this study demonstrates that the proposed methodology can be used to assess public perspectives on various energy resources

Representation of Boreal Winter MJO and Its Teleconnection in a Dynamical Ensemble Seasonal Prediction System

This study examines the representation of the Madden-Julian oscillation (MJO) and its teleconnection in boreal winter in the Global Seasonal Forecast System, version 5 (GloSea5), using 20 years (1991-2010) of hindcast data. The sensitivity of the performance to the polarity of El Nino-Southern Oscillation (ENSO) is also investigated. The real-time multivariate MJO index of Wheeler and Hendon is used to assess MJO prediction skill while intraseasonal 200-hPa streamfunction anomalies are used to evaluate the MJO teleconnection. GloSea5 exhibits significant MJO prediction skill up to 25 days of forecast lead time. MJO prediction skill in GloSea5 also depends on initial MJO phases, with relatively enhanced (degraded) performance when the initial MJO phase is 2 or 3 (8 or 1) during the first 2 weeks of the hindcast period. GloSea5 depicts the observed MJO teleconnection patterns in the extratropics realistically up to 2 weeks albeit weaker than the observed. The ENSO-associated basic-state changes in the tropics and in the midlatitudes are reasonably represented in GloSea5. MJO prediction skill during the first 2 weeks of the hindcast is slightly higher in neutral and La Nina years than in El Nino years, especially in the upper-level zonal wind anomalies. Presumably because of the better representation of MJO-related tropical heating anomalies, the Northern Hemispheric MJO teleconnection patterns in neutral and La Nina years are considerably better than those in El Nino years

Optogenetic control of mRNA localization and translation in live cells

Despite efforts to visualize the spatio–temporal dynamics of single messenger RNAs, the ability to precisely control their function has lagged. This study presents an optogenetic approach for manipulating the localization and translation of specific mRNAs by trapping them in clusters. This clustering greatly amplified reporter signals, enabling endogenous RNA–protein interactions to be clearly visualized in single cells. Functionally, this sequestration reduced the ability of mRNAs to access ribosomes, markedly attenuating protein synthesis. A spatio–temporally resolved analysis indicated that sequestration of endogenous β-actin mRNA attenuated cell motility through the regulation of focal-adhesion dynamics. These results suggest a mechanism highlighting the indispensable role of newly synthesized β-actin protein for efficient cell migration. This platform may be broadly applicable for use in investigating the spatio–temporal activities of specific mRNAs in various biological processes.11Nsciescopu

CASS: A distributed network clustering algorithm based on structure similarity for large-scale network.

As the size of networks increases, it is becoming important to analyze large-scale network data. A network clustering algorithm is useful for analysis of network data. Conventional network clustering algorithms in a single machine environment rather than a parallel machine environment are actively being researched. However, these algorithms cannot analyze large-scale network data because of memory size issues. As a solution, we propose a network clustering algorithm for large-scale network data analysis using Apache Spark by changing the paradigm of the conventional clustering algorithm to improve its efficiency in the Apache Spark environment. We also apply optimization approaches such as Bloom filter and shuffle selection to reduce memory usage and execution time. By evaluating our proposed algorithm based on an average normalized cut, we confirmed that the algorithm can analyze diverse large-scale network datasets such as biological, co-authorship, internet topology and social networks. Experimental results show that the proposed algorithm can develop more accurate clusters than comparative algorithms with less memory usage. Furthermore, we confirm the proposed optimization approaches and the scalability of the proposed algorithm. In addition, we validate that clusters found from the proposed algorithm can represent biologically meaningful functions

Relationship between economic loss and anxiety during the Coronavirus disease 2019 pandemic: moderating effects of knowledge, gratitude, and perceived stress

Objectives: The prolonged coronavirus disease 2019 (COVID-19) pandemic has caused individuals to suffer economic losses, in particular due to the implementation of intensive quarantine policies. Economic loss can cause anxiety and has a negative psychological impact on individuals, worsening their mental health and satisfaction with life. We examined the protective and risk factors that can influence the relationship between economic loss and anxiety during the COVID-19 pandemic. Methods: Panel data from 911 participants were collected in April and May 2020 and again 6 months later. We analyzed the relationship between economic loss and anxiety and investigated the moderating effects of knowledge about COVID-19, gratitude, and perceived stress. Moreover, we investigated whether there were any changes in moderating effects over time or in different demographic groups. Results: In the early stages of the spread of COVID-19, gratitude (B = –0.0211, F = 4.8130, p < 0.05) and perceived stress (B = 0.0278, F = 9.3139, p < 0.01) had moderating effects on the relationship between economic loss and anxiety. However, after 6 months, only perceived stress had a significant moderating effect (B = 0.0265, F = 7.8734, p < 0.01). Conclusion: In the early stages of COVID-19, lower levels of gratitude and higher perceived stress led to greater anxiety. In later stages of the prolonged pandemic, only perceived stress had a continued moderating effect on the relationship between economic loss and anxiety. This study suggests that psychological interventions to reduce perceived stress are needed to treat the possible adverse effects of the spread of infectious diseases on mental health