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Thomas Mock, Robert P Otillar, Jan Strauss, Mark McMullan, Pirita Paajanen, Jeremy Schmutz, Asaf Salamov, Remo Sanges, Andrew Toseland, Ben J Ward, Andrew E Allen, Christopher L Dupont, Stephan Frickenhaus, Florian Maumus, Alaguraj Veluchamy, Taoyang Wu, Kerrie W Barry, Angela Falciatore, Maria I Ferrante, Antonio E Fortunato, Gernot Glöckner, Ansgar Gruber, Rachel Hipkin, Michael G Janech, Peter G Kroth, Florian Leese, Erika A Lindquist, Barbara R Lyon, Joel Martin, Christoph Mayer, Micaela Parker, Hadi Quesneville, James A Raymond, Christiane Uhlig, Ruben E Valas, Klaus U Valentin, Alexandra Z Worden, E Virginia Armbrust, Matthew D Clark, Chris Bowler, Beverley R Green, Vincent Moulton, Cock van Oosterhout, Igor V Grigoriev
The Southern Ocean houses a diverse and productive community of organisms. Unicellular eukaryotic diatoms are the main primary producers in this environment, where photosynthesis is limited by low concentrations of dissolved iron and large seasonal fluctuations in light, temperature and the extent of sea ice. How diatoms have adapted to this extreme environment is largely unknown. Here we present insights into the genome evolution of a cold-adapted diatom from the Southern Ocean, Fragilariopsis cylindrus, based on a comparison with temperate diatoms...
January 16, 2017: Nature
Kenneth Haug, Reza M Salek, Christoph Steinbeck
Chemical Biology employs chemical synthesis, analytical chemistry and other tools to study biological systems. Recent advances in both molecular biology such as next generation sequencing (NGS) have led to unprecedented insights towards the evolution of organisms' biochemical repertoires. Because of the specific data sharing culture in Genomics, genomes from all kingdoms of life become readily available for further analysis by other researchers. While the genome expresses the potential of an organism to adapt to external influences, the Metabolome presents a molecular phenotype that allows us to asses the external influences under which an organism exists and develops in a dynamic way...
January 13, 2017: Current Opinion in Chemical Biology
Francisco J Corpas, Juan B Barroso, José M Palma, Marta Rodriguez-Ruiz
Although peroxisomes are very simple organelles, research on different species has provided us with an understanding of their importance in terms of cell viability. In addition to the significant role played by plant peroxisomes in the metabolism of reactive oxygen species (ROS), data gathered over the last two decades show that these organelles are an endogenous source of nitric oxide (NO) and related molecules called reactive nitrogen species (RNS). Molecules such as NO and H2O2 act as retrograde signals among the different cellular compartments, thus facilitating integral cellular adaptation to physiological and environmental changes...
January 3, 2017: Redox Biology
Fangjie Mao, Guomo Zhou, Pingheng Li, Huaqiang Du, Xiaojun Xu, Yongjun Shi, Lufeng Mo, Yufeng Zhou, Guoqing Tu
The selective cutting method currently used in Moso bamboo forests has resulted in a reduction of stand productivity and carbon sequestration capacity. Given the time and labor expense involved in addressing this problem manually, simulation using an ecosystem model is the most suitable approach. The BIOME-BGC model was improved to suit managed Moso bamboo forests, which was adapted to include age structure, specific ecological processes and management measures of Moso bamboo forest. A field selective cutting experiment was done in nine plots with three cutting intensities (high-intensity, moderate-intensity and low-intensity) during 2010-2013, and biomass of these plots was measured for model validation...
January 13, 2017: Journal of Environmental Management
B W C Tse, M Volpert, E Ratther, N Stylianou, M Nouri, K McGowan, M L Lehman, S J McPherson, M Roshan-Moniri, M S Butler, J Caradec, C Y Gregory-Evans, J McGovern, R Das, M Takhar, N Erho, M Alshalafa, E Davicioni, E M Schaeffer, R B Jenkins, A E Ross, R J Karnes, R B Den, L Fazli, P A Gregory, M E Gleave, E D Williams, P S Rennie, R Buttyan, J H Gunter, L A Selth, P J Russell, C C Nelson, B G Hollier
Recent evidence has implicated the transmembrane co-receptor neuropilin-1 (NRP1) in cancer progression. Primarily known as a regulator of neuronal guidance and angiogenesis, NRP1 is also expressed in multiple human malignancies, where it promotes tumor angiogenesis. However, non-angiogenic roles of NRP1 in tumor progression remain poorly characterized. In this study, we define NRP1 as an androgen-repressed gene whose expression is elevated during the adaptation of prostate tumors to androgen-targeted therapies (ATTs), and subsequent progression to metastatic castration-resistant prostate cancer (mCRPC)...
January 16, 2017: Oncogene
Marco Prinz, Josef Priller
The CNS is protected by the immune system, including cells that reside directly within the CNS and help to ensure proper neural function, as well as cells that traffic into the CNS with disease. The CNS-resident immune system is comprised mainly of innate immune cells and operates under homeostatic conditions. These myeloid cells in the CNS parenchyma and at CNS-periphery interfaces are highly specialized but also extremely plastic cells that immediately react to any changes in CNS homeostasis and become reactive in the context of neurodegenerative disorders such as Alzheimer's disease or Parkinson's disease...
January 16, 2017: Nature Neuroscience
Carlos Maillo, Judit Martín, David Sebastián, Maribel Hernández-Alvarez, Mar García-Rocha, Oscar Reina, Antonio Zorzano, Mercedes Fernandez, Raúl Méndez
The cytoplasmic polyadenylation element-binding (CPEB) proteins regulate pre-mRNA processing and translation of CPE-containing mRNAs in early embryonic development and synaptic activity. However, specific functions in adult organisms are poorly understood. Here we show that CPEB4 is required for adaptation to high-fat-diet- and ageing-induced endoplasmic reticulum (ER) stress, and subsequent hepatosteatosis. Stress-activated liver CPEB4 expression is dual-mode regulated. First, Cpeb4 mRNA transcription is controlled by the circadian clock, and then its translation is regulated by the unfolded protein response (UPR) through upstream open reading frames within the 5'UTR...
January 16, 2017: Nature Cell Biology
Q Y Yang, T Chen, Y B Chen, D L Lan
The NOD-like receptor (NLR) family caspase recruitment domain-containing 5 (NLRC5) is one of the newly discovered and largest NLR family members. The NLRC5 has recently received extensive attention because of its important role in regulating innate and adaptive immune responses. The NLRC5 in many vertebrates, such as humans, mice, cattle, and horses, has already been proven and studied. However, the NLRC5 gene characteristics of pigs remain unclear. Thus, we completely cloned the NLRC5 cDNA sequence of the pig using the rapid amplification of cDNA ends(RACE) technology...
December 1, 2016: Polish Journal of Veterinary Sciences
Ben Niu, Yanjun Liu, Guangdeng Zong, Zhaoyu Han, Jun Fu
In this paper, a new adaptive approximation-based tracking controller design approach is developed for a class of uncertain nonlinear switched lower-triangular systems with an output constraint using neural networks (NNs). By introducing a novel barrier Lyapunov function (BLF), the constrained switched system is first transformed into a new system without any constraint, which means the control objectives of the both systems are equivalent. Then command filter technique is applied to solve the so-called "explosion of complexity" problem in traditional backstepping procedure, and radial basis function NNs are directly employed to model the unknown nonlinear functions...
January 16, 2017: IEEE Transactions on Cybernetics
Luyang Li, Yun-Hui Liu, Tianjiao Jiang, Kai Wang, Mu Fang
Despite tremendous efforts made for years, trajectory tracking control (TC) of a nonholonomic mobile robot (NMR) without global positioning system remains an open problem. The major reason is the difficulty to localize the robot by using its onboard sensors only. In this paper, a newly designed adaptive trajectory TC method is proposed for the NMR without its position, orientation, and velocity measurements. The controller is designed on the basis of a novel algorithm to estimate position and velocity of the robot online from visual feedback of an omnidirectional camera...
January 16, 2017: IEEE Transactions on Cybernetics
Wei Wang, Shaocheng Tong
This paper studies the adaptive fuzzy bounded control problem for leader-follower multiagent systems, where each follower is modeled by the uncertain nonlinear strict-feedback system. Combining the fuzzy approximation with the dynamic surface control, an adaptive fuzzy control scheme is developed to guarantee the output consensus of all agents under directed communication topologies. Different from the existing results, the bounds of the control inputs are known as a priori, and they can be determined by the feedback control gains...
January 10, 2017: IEEE Transactions on Cybernetics
Huanqing Wang, Peter Xiaoping Liu, Shichao Liu
This paper considers the master and slave synchronization control for bilateral teleoperation systems with time delay and backlash-like hysteresis. Based on radial basis functions neural networks' approximation capabilities, two improved adaptive neural control approaches are developed. By Lyapunov stability analysis, the position and velocity tracking errors are guaranteed to converge to a small neighborhood of the origin. The contributions of this paper can be summarized as follows: 1) by using the matrix norm established using the weight vector of neural networks as the estimated parameters, two novel control schemes are developed and 2) the hysteresis inverse is not required in the proposed controllers...
January 10, 2017: IEEE Transactions on Cybernetics
Yuanheng Zhu, Dongbin Zhao, Xiong Yang, Qichao Zhang
Sum of squares (SOS) polynomials have provided a computationally tractable way to deal with inequality constraints appearing in many control problems. It can also act as an approximator in the framework of adaptive dynamic programming. In this paper, an approximate solution to the H∞ optimal control of polynomial nonlinear systems is proposed. Under a given attenuation coefficient, the Hamilton-Jacobi-Isaacs equation is relaxed to an optimization problem with a set of inequalities. After applying the policy iteration technique and constraining inequalities to SOS, the optimization problem is divided into a sequence of feasible semidefinite programming problems...
January 10, 2017: IEEE Transactions on Cybernetics
Ke Yan, Lu Kou, David Zhang
Domain adaptation algorithms are useful when the distributions of the training and the test data are different. In this paper, we focus on the problem of instrumental variation and time-varying drift in the field of sensors and measurement, which can be viewed as discrete and continuous distributional change in the feature space. We propose maximum independence domain adaptation (MIDA) and semi-supervised MIDA to address this problem. Domain features are first defined to describe the background information of a sample, such as the device label and acquisition time...
January 16, 2017: IEEE Transactions on Cybernetics
Wei Liu, Jie Huang
This paper studies the cooperative global robust output regulation problem for a class of heterogeneous second-order nonlinear uncertain multiagent systems with jointly connected switching networks. The main contributions consist of the following three aspects. First, we generalize the result of the adaptive distributed observer from undirected jointly connected switching networks to directed jointly connected switching networks. Second, by performing a new coordinate and input transformation, we convert our problem into the cooperative global robust stabilization problem of a more complex augmented system via the distributed internal model principle...
January 11, 2017: IEEE Transactions on Neural Networks and Learning Systems
E Emary, Hossam M Zawbaa, Crina Grosan
In this paper, a variant of gray wolf optimization (GWO) that uses reinforcement learning principles combined with neural networks to enhance the performance is proposed. The aim is to overcome, by reinforced learning, the common challenge of setting the right parameters for the algorithm. In GWO, a single parameter is used to control the exploration/exploitation rate, which influences the performance of the algorithm. Rather than using a global way to change this parameter for all the agents, we use reinforcement learning to set it on an individual basis...
January 10, 2017: IEEE Transactions on Neural Networks and Learning Systems
Elliot Greenwald, Christoph Maier, Qihong Wang, Robert Beaulieu, Ralph Etienne-Cummings, Gert Cauwenberghs, Nitish Thakor
An 8-channel current steerable, multi-phasic neural stimulator with on-chip current DAC calibration and residue nulling for precise charge balancing is presented. Each channel consists of two sub-binary radix DACs followed by wide-swing, high output impedance current buffers providing time-multiplexed source and sink outputs for anodic and cathodic stimulation. A single integrator is shared among channels and serves to calibrate DAC coefficients and to closely match the anodic and cathodic stimulation phases...
January 16, 2017: IEEE Transactions on Biomedical Circuits and Systems
Martin Damrath, Sebastian Korte, Peter Hoeher
This paper introduces the equivalent discrete-time channel model (EDTCM) to the area of diffusion-based molecular communication (DBMC). Emphasize is on an absorbing receiver, which is based on the so-called first passage time concept. In the wireless communications community the EDTCM is well known. Therefore, it is anticipated that the EDTCM improves the accessibility of DBMC and supports the adaptation of classical wireless communication algorithms to the area of DBMC. Furthermore, the EDTCM has the capability to provide a remarkable reduction of computational complexity compared to random walk based DBMC simulators...
January 10, 2017: IEEE Transactions on Nanobioscience
Jiahao Pang, Gene Cheung
Inverse imaging problems are inherently underdetermined, and hence it is important to employ appropriate image priors for regularization. One recent popular prior- the graph Laplacian regularizer-assumes that the target pixel patch is smooth with respect to an appropriately chosen graph. However, the mechanisms and implications of imposing the graph Laplacian regularizer on the original inverse problem are not well understood. To address this problem, in this paper we interpret neighborhood graphs of pixel patches as discrete counterparts of Riemannian manifolds and perform analysis in the continuous domain, providing insights into several fundamental aspects of graph Laplacian regularization for image denoising...
January 11, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Lukas Krasula, Patrick Le Callet, Karel Fliegel, Milos Klima
Most of the effort in image quality assessment (QA) has been so far dedicated to the degradation of the image. However, there are also many algorithms in the image processing chain that can enhance the quality of an input image. These include procedures for contrast enhancement, deblurring, sharpening, up-sampling, denoising, transfer function compensation, etc. In this work, possible strategies for the quality assessment of sharpened images are investigated. This task is not trivial because the sharpening techniques can increase the perceived quality, as well as introduce artifacts leading to the quality drop (over-sharpening)...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
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