Low-frequency Gravitational Wave Detection via Double Optical Clocks in Space

We propose a Doppler tracking system for gravitational wave detection via Double Optical Clocks in Space (DOCS). In this configuration two spacecrafts (each containing an optical clock) are launched to space for Doppler shift observations. Compared to the similar attempt of gravitational wave detection in the Cassini mission, the radio signal of DOCS that contains the relative frequency changes avoids completely noise effects due for instance to troposphere, ionosphere, ground-based antenna and transponder. Given the high stabilities of the two optical clocks (Allan deviation $\sim 4.1\times 10^{-17}$ @ 1000 s), an overall estimated sensitivity of $5 \times 10^{-19}$ could be achieved with an observation time of 2 years, and would allow to detect gravitational waves in the frequency range from $\sim 10^{-4}$ Hz to $\sim 10^{-2}$ Hz.Comment: 18 pages, 2 figure

A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games

This paper proposes novel, end-to-end deep reinforcement learning algorithms for learning two-player zero-sum Markov games. Our objective is to find the Nash Equilibrium policies, which are free from exploitation by adversarial opponents. Distinct from prior efforts on finding Nash equilibria in extensive-form games such as Poker, which feature tree-structured transition dynamics and discrete state space, this paper focuses on Markov games with general transition dynamics and continuous state space. We propose (1) Nash DQN algorithm, which integrates DQN with a Nash finding subroutine for the joint value functions; and (2) Nash DQN Exploiter algorithm, which additionally adopts an exploiter for guiding agent's exploration. Our algorithms are the practical variants of theoretical algorithms which are guaranteed to converge to Nash equilibria in the basic tabular setting. Experimental evaluation on both tabular examples and two-player Atari games demonstrates the robustness of the proposed algorithms against adversarial opponents, as well as their advantageous performance over existing methods

An Immune Detector-Based Method for the Diagnosis of Compound Faults in a Petrochemical Plant

Aiming at the serious overlap of traditional dimensionless indices in the diagnosis of compound faults in petrochemical plants, we use genetic programming to construct optimal indices for that purpose. In order to solve the problem of losing some useful fault feature information due to classification processing, during the generation of the dimensionless index immune detector, such as reduction and clustering, we propose an integrated diagnosis method using each dimensionless index immune detector. Simulation results show that this method has high diagnostic accuracy

Multiobjective Image Color Quantization Algorithm Based on Self-Adaptive Hybrid Differential Evolution

In recent years, some researchers considered image color quantization as a single-objective problem and applied heuristic algorithms to solve it. This paper establishes a multiobjective image color quantization model with intracluster distance and intercluster separation as its objectives. Inspired by a multipopulation idea, a multiobjective image color quantization algorithm based on self-adaptive hybrid differential evolution (MoDE-CIQ) is then proposed to solve this model. Two numerical experiments on four common test images are conducted to analyze the effectiveness and competitiveness of the multiobjective model and the proposed algorithm

Thermal management of using controlled crystallization supercooled PCM in space heating applications for different heating profiles in the UK

Supercooled Sodium acetate trihydrate (SAT) allows the latent heat can be released when it is externally triggered regardless of the supercooling degree. Thus, the implementation of SAT into heating systems can eliminate the negative effects of weather variation and increase the utilization of solar energy by storing the heat for days. However, supercooled PCMs can lose a serious amount of latent heat when their temperature falls to ambient temperature. Moreover, the poor heat conductivity of the SAT can cause providing insufficient temperature in the houses for different heating profiles which requires auxiliary heating. In this study, the dynamic thermal behaviour of a supercooled PCM-immersed storage tank for heating different dwellings is investigated based on different activation orders of the PCM tubes. The controlled PCM activation order shows that the hot water supply temperature can be increased compared to the activation of all tubes at midnight. Controlled triggering resulted in performance improvement in all heating profiles by an increment of 1.5 °C, but it is more promising for the Eco-house heating profile as it reaches 4.3 °C. Moreover, this method reduces the daily heat loss from the PCM storage tank by up to 1.3 kWh. It is also found that the PCM loses its 35% of latent energy after three days of storage

A Convergent Differential Evolution Algorithm with Hidden Adaptation Selection for Engineering Optimization

Many improved differential Evolution (DE) algorithms have emerged as a very competitive class of evolutionary computation more than a decade ago. However, few improved DE algorithms guarantee global convergence in theory. This paper developed a convergent DE algorithm in theory, which employs a self-adaptation scheme for the parameters and two operators, that is, uniform mutation and hidden adaptation selection (haS) operators. The parameter self-adaptation and uniform mutation operator enhance the diversity of populations and guarantee ergodicity. The haS can automatically remove some inferior individuals in the process of the enhancing population diversity. The haS controls the proposed algorithm to break the loop of current generation with a small probability. The breaking probability is a hidden adaptation and proportional to the changes of the number of inferior individuals. The proposed algorithm is tested on ten engineering optimization problems taken from IEEE CEC2011

Direct-expansion solar-assisted heat pump coupled with crystallisation-controlled supercooled PCM for shifting building electricity demand

This paper proposes a novel approach for improving the performance of a direct-expansion solar-assisted heat pump (DX-SAHP) system by integrating a crystallisation controllable phase change material (PCM) and building energy demand shifting strategy. The proposed system aims to reduce buildings' energy consumption while utilizing solar energy efficiently. Sodium acetate trihydrate (SAT) as the crystallisation controllable supercooled PCM has a promising feature of releasing the stored latent heat when it is externally triggered, allowing the user to control the stored heat whenever needed. In the study, the PCM can store the thermal energy generated by the DX-SAHP during peak solar hours in an efficient way. This stored energy can be released when solar energy is unavailable, but the heating is requested. This approach not only reduces the load on the heat pump system but also makes efficient use of the stored thermal energy by crystallisation controllable PCM. A detailed controlling methodology of the system is given, and heating output is controlled considering the level of solar irradiance. The proposed system was modelled and simulated using MATLAB, and the results show that the integration of crystallisation controllable PCM and building demand shifting strategy can significantly reduce the energy consumption of the buildings. On the low solar radiation day, the COP improvement compared to the air source heat pump system was found 9.4%, this improvement value can reach 77% on high solar radiation days. The system can also effectively utilize solar energy and reduce the overall carbon footprint of buildings

Aflatoxin B1, zearalenone and deoxynivalenol in feed ingredients and complete feed from different Province in China

Abstract Background The current study was carried out to provide a reference for monitory of aflatoxin B1 (AFB1), zearalenone (ZEN) and deoxynivalenol (DON) contamination in feed ingredients and complete feeds were collected from different Province in China from 2013 to 2015. Methods A total of 443 feed ingredients, including 220 corn, 24 wheat, 24 domestic distillers dried grains with soluble (DDGS), 55 bran, 20 wheat shorts and red dog, 37 imported DDGS, 34 corn germ meal and 29 soybean meal as well as 127 complete feeds including 25 pig complete feed (powder), 90 pig complete feed (pellet), six duck complete feed and six cattle complete feed were randomly collected from different Province in China, respectively, by high-performance chromatography in combined with UV or fluorescence analysis. Results The incidence rates of AFB1, ZEN and DON contamination of feed ingredients and complete feeds were 80.8, 92.3 and 93.9 %, respectively. The percentage of positive samples for DON ranged from 66.7 to 100 %. Domestic DDGS and imported DDGS presented the most serious contamination AFB1, ZEN and DON contamination levels of feeds ranged from 61.5 to 100 %, indicated that serious contamination over the studied 3-year period. Conclusion The current data provide clear evidence that AFB1, ZEN and DON contamination of feed ingredients and complete feeds in different Province in China is serious and differs over past 3-year. The use of corn, domestic DDGS, imported DDGS and corn germ meal, which may be contaminated with these three mycotoxins, as animal feed may triggered a health risk for animal. Feeds are most contaminated with DON followed by ZEN and AFB1. Mycotoxins contamination in feed ingredients and complete feeds should be monitored routinely in China

Transcriptome analysis of Deinagkistrodon acutus venomous gland focusing on cellular structure and functional aspects using expressed sequence tags

BACKGROUND: The snake venom gland is a specialized organ, which synthesizes and secretes the complex and abundant toxin proteins. Though gene expression in the snake venom gland has been extensively studied, the focus has been on the components of the venom. As far as the molecular mechanism of toxin secretion and metabolism is concerned, we still knew a little. Therefore, a fundamental question being arisen is what genes are expressed in the snake venom glands besides many toxin components? RESULTS: To examine extensively the transcripts expressed in the venom gland of Deinagkistrodon acutus and unveil the potential of its products on cellular structure and functional aspects, we generated 8696 expressed sequence tags (ESTs) from a non-normalized cDNA library. All ESTs were clustered into 3416 clusters, of which 40.16% of total ESTs belong to recognized toxin-coding sequences; 39.85% are similar to cellular transcripts; and 20.00% have no significant similarity to any known sequences. By analyzing cellular functional transcripts, we found high expression of some venom related genes and gland-specific genes, such as calglandulin EF-hand protein gene and protein disulfide isomerase gene. The transcripts of creatine kinase and NADH dehydrogenase were also identified at high level. Moreover, abundant cellular structural proteins similar to mammalian muscle tissues were also identified. The phylogenetic analysis of two snake venom toxin families of group III metalloproteinase and serine protease in suborder Colubroidea showed an early single recruitment event in the viperids evolutionary process. CONCLUSION: Gene cataloguing and profiling of the venom gland of Deinagkistrodon acutus is an essential requisite to provide molecular reagents for functional genomic studies needed for elucidating mechanisms of action of toxins and surveying physiological events taking place in the very specialized secretory tissue. So this study provides a first global view of the genetic programs for the venom gland of Deinagkistrodon acutus described so far and an insight into molecular mechanism of toxin secreting. All sequences data reported in this paper have been submitted into the public database [GenBank: DV556511-DV565206]