COLD1 confers chilling tolerance in rice.

Rice is sensitive to cold and can be grown only in certain climate zones. Human selection of japonica rice has extended its growth zone to regions with lower temperature, while the molecular basis of this adaptation remains unknown. Here, we identify the quantitative trait locus COLD1 that confers chilling tolerance in japonica rice. Overexpression of COLD1(jap) significantly enhances chilling tolerance, whereas rice lines with deficiency or downregulation of COLD1(jap) are sensitive to cold. COLD1 encodes a regulator of G-protein signaling that localizes on plasma membrane and endoplasmic reticulum (ER). It interacts with the G-protein α subunit to activate the Ca(2+) channel for sensing low temperature and to accelerate G-protein GTPase activity. We further identify that a SNP in COLD1, SNP2, originated from Chinese Oryza rufipogon, is responsible for the ability of COLD(jap/ind) to confer chilling tolerance, supporting the importance of COLD1 in plant adaptation.

Optimal Tracking Control of Heterogeneous MASs Using Event-Driven Adaptive Observer and Reinforcement Learning.

This article considers the output tracking control problem of nonidentical linear multiagent systems (MASs) using a model-free reinforcement learning (RL) algorithm, where partial followers have no prior knowledge of the leader's information. To lower the communication and computing burden among agents, an event-driven adaptive distributed observer is proposed to predict the leader's system matrix and state, which consists of the estimated value of relative states governed by an edge-based predictor. Meanwhile, the integral input-based triggering condition is exploited to decide whether to transmit its private control input to its neighbors. Then, an RL-based state feedback controller for each agent is developed to solve the output tracking control problem, which is further converted into the optimal control problem by introducing a discounted performance function. Inhomogeneous algebraic Riccati equations (AREs) are derived to obtain the optimal solution of AREs. An off-policy RL algorithm is used to learn the solution of inhomogeneous AREs online without requiring any knowledge of the system dynamics. Rigorous analysis shows that under the proposed event-driven adaptive observer mechanism and RL algorithm, all followers are able to synchronize the leader's output asymptotically. Finally, a numerical simulation is demonstrated to verify the proposed approach in theory.

Resilient Asynchronous State Estimation for Markovian Jump Neural Networks Subject to Stochastic Nonlinearities and Sensor Saturations.

This article studies the problem of dissipativity-based asynchronous state estimation for a class of discrete-time Markov jump neural networks subject to randomly occurring nonlinearities, sensor saturations, and stochastic parameter uncertainties. First, two stochastic nonlinearities occurring in the system are described by statistical means and obey two Bernoulli processes independently. Then, the hidden Markov model is used to characterize the real communication environment closely between the designed estimator and the system model due to the networked-induced phenomenons that also lead to randomly occurring parametric uncertainties of the estimator considered modeled by two Bernoulli processes. A new criterion is established to guarantee that the resulting error system is stochastically stable with predefined dissipativity performance. Finally, we provide a simulation example to validate the theoretical analysis.

Event-Based Dissipative Filtering of Markovian Jump Neural Networks Subject to Incomplete Measurements and Stochastic Cyber-Attacks.

In this article, the dissipativity-based filtering of the Markovian jump neural networks subject to incomplete measurements and deception attacks is investigated by adopting an event-triggered communication strategy, where the attackers are supposed to occur in a random fashion but obey the Bernoulli distribution. Consider that the information of the system mode is transmitted to the filter over the communication network that is vulnerable to external attacks, which may lead to the undesired performance of the resulting system by injecting malicious information from the attackers. As a result, the filter has difficulty completing information from the original system. Besides, an event-triggered communication mechanism is introduced to reduce the communication frequency between data transmission due to the limited network resources, and different triggering conditions corresponding to different jump modes are developed. Then, based on the above considerations, the sufficient condition is derived to ensure the stochastic stability and dissipativity of the resulting augmented system although the deception attacks and incomplete information exist. A numerical simulated example is provided to verify the theoretical analysis.

Synchronization of Coupled Harmonic Oscillators With Asynchronous Intermittent Communication.

This paper adopts two different approaches, the small-gain technique and the integral quadratic constraints (IQCs), to investigate the synchronization problem of coupled harmonic oscillators (CHOs) via an event-triggered control strategy in a directed graph. First, a novel control protocol is proposed such that every state signal of the CHO decides when to exchange information with its neighbors asynchronously. Then, the resulting closed-loop system based on the designed control protocol is converted into a feedback interconnection of a linear system and a bounded operator, and the stable condition of the feedback interconnection is presented by employing the small-gain technique. In order to better describe the relationship between the input and output, the IQCs theorem is applied to derive the stable condition on the basis of the Kalman-Yakubovich-Popov lemma. Finally, a simulation example is provided to verify the proposed new algorithms.

Hidden-Markov-Model-Based Asynchronous Filter Design of Nonlinear Markov Jump Systems in Continuous-Time Domain.

This paper addresses the dissipative asynchronous filtering problem for a class of Takagi-Sugeno fuzzy Markov jump systems in the continuous-time domain. The hidden Markov model is applied to describe the asynchronous situation between the designed filter and the original system. Based on the stochastic Lyapunov function, a sufficient condition is developed to guarantee the stochastic stability of the filtering error systems with a given dissipative performance. Two different methods for the existence of desired filter are established. Due to the Finsler's lemma, the second approach has fewer variables to decide and brings less conservatism than the first one. Finally, an example is provided to demonstrate the correctness and advantage of the proposed approaches.

Dynamic Interactions of Plant CNGC Subunits and Calmodulins Drive Oscillatory Ca2+ Channel Activities.

Calcium is a universal signal in all eukaryotes, but the mechanism for encoding calcium signatures remains largely unknown. Calcium oscillations control pollen tube growth and fertilization in flowering plants, serving as a model for dissecting the molecular machines that mediate calcium fluctuations. We report that pollen-tube-specific cyclic nucleotide-gated channels (CNGC18, CNGC8, and CNGC7) together with calmodulin 2 (CaM2) constitute a molecular switch that either opens or closes the calcium channel depending on cellular calcium levels. Under low calcium, calcium-free calmodulin 2 (Apo-CaM2) interacts with CNGC18-CNGC8 complex, leading to activation of the influx channel and consequently increasing cytosolic calcium levels. Calcium-bound CaM2 dissociates from CNGC18/8 heterotetramer, closing the channel and initiating a downturn of cellular calcium levels. We further reconstituted the calcium oscillator in HEK293 cells, supporting the model that Ca2+-CaM-dependent regulation of CNGC channel activity provides an auto-regulatory feedback mechanism for calcium oscillations during pollen tube growth.

Improving Haptic Transparency for Uncertain Virtual Environments Using Adaptive Control and Gain-Scheduled Prediction.

The realism or transparency of haptic interfaces is becoming more critical as they are applied to training in fields like minimally invasive surgery (MIS). Surgical training simulators must provide a transparent virtual environment (VE) at a high update rate. Complex, deformable, cuttable tissue models have nonlinear dynamics and are computationally expensive, making it difficult to provide sufficient update rates. The objective of this work is to improve the transparency for this type of VE by formulating the unknown nonlinear dynamics as a quasi-linear parameter varying (LPV) system and designing a predictor to provide an output at a much higher update rate. An adaptive controller based on gain-scheduled prediction is considered for a nonlinear haptic device and a nonlinear, delayed, and sampled VE. The predictor uses feedback from the more accurate but slow-updating VE to update a simplified dynamic model. The predictor is designed based on numerical solutions to a linear matrix inequality derived using Lyapunov-based methods. Experimental results demonstrate the effectiveness of the gain-scheduled predictor approach and compare it to previous work using a constant-gain predictor. The gain-scheduled predictor results in significant performance improvements compared to a haptic system without prediction, but less significant improvement compared to the constant-gain approach.

G-protein ßγ subunits determine grain size through interaction with MADS-domain transcription factors in rice.

The simultaneous improvement of grain quality and yield of cereal crops is a major challenge for modern agriculture. Here we show that a rice grain yield quantitative trait locus qLGY3 encodes a MADS-domain transcription factor OsMADS1, which acts as a key downstream effector of G-protein ßγ dimers. The presence of an alternatively spliced protein OsMADS1lgy3 is shown to be associated with formation of long and slender grains, resulting in increases in both grain quality and yield potential of rice. The Gγ subunits GS3 and DEP1 interact directly with the conserved keratin-like domain of MADS transcription factors, function as cofactors to enhance OsMADS1 transcriptional activity and promote the co-operative transactivation of common target genes, thereby regulating grain size and shape. We also demonstrate that combining OsMADS1 lgy3 allele with high-yield-associated dep1-1 and gs3 alleles represents an effective strategy for simultaneously improving both the productivity and end-use quality of rice.

Non-canonical regulation of SPL transcription factors by a human OTUB1-like deubiquitinase defines a new plant type rice associated with higher grain yield.

Achieving increased grain productivity has long been the overriding focus of cereal breeding programs. The ideotype approach has been used to improve rice yield potential at the International Rice Research Institute and in China. However, the genetic basis of yield-related traits in rice remains unclear. Here, we show that a major quantitative trait locus, qNPT1, acts through the determination of a 'new plant type' (NPT) architecture characterized by fewer tillers, sturdier culms and larger panicles, and it encodes a deubiquitinating enzyme with homology to human OTUB1. Downregulation of OsOTUB1 enhances meristematic activity, resulting in reduced tiller number, increased grain number, enhanced grain weight and a consequent increase in grain yield in rice. Unlike human OTUB1, OsOTUB1 can cleave both K48- and K63-linked polyubiquitin. OsOTUB1 interacts with the E2 ubiquitin-conjugating protein OsUBC13 and the squamosa promoter-binding protein-like transcription factor OsSPL14. OsOTUB1 and OsSPL14 share common target genes, and their physical interaction limits K63-linked ubiquitination (K63Ub) of OsSPL14, which in turn promotes K48Ub-dependent proteasomal degradation of OsSPL14. Conversely, loss-of-function of OsOTUB1 is correlated with the accumulation of high levels of OsSPL14, resulting in the NPT architecture. We also demonstrated that pyramiding of high-yielding npt1 and dep1-1 alleles provides a new strategy for increasing rice yield potential above what is currently achievable.

Iron-nitrogen-activated carbon as cathode catalyst to improve the power generation of single-chamber air-cathode microbial fuel cells.

In order to improve the performance of microbial fuel cell (MFC), iron-nitrogen-activated carbon (Fe-N-C) as an excellent oxygen reduction reaction (ORR) catalyst was prepared here using commercial activated carbon (AC) as matrix and employed in single chamber MFC. In MFC, the maximum power density increased to 2437±55 mW m(-2), which was 2 times of that with AC. The open circuit potential (OCP) of Fe-N-C cathode (0.47) was much higher than that of AC cathode (0.21 V). The R0 of Fe-N-C decreased by 47% from 14.36 Ω (AC) to 7.6 Ω (Fe-N-C). From X-ray photoelectron spectroscopy (XPS), pyridinic nitrogen, quaternary nitrogen and iron species were present, which played an important role in the ORR performance of Fe-N-C. These results demonstrated that the as-prepared Fe-N-C material provided a potential alternative to Pt in AC air cathode MFC for relatively desirable energy generation and wastewater treatment.

Hollow-spherical Co/N-C nanoparticle as an efficient electrocatalyst used in air cathode microbial fuel cell.

The hollow-spherical Co/N-C nanoparticle, which is synthesized via a simple hydrothermal reaction followed by heat treatment, is firstly used as electrocatalyst for oxygen reduction reaction (ORR) in air-cathode microbial fuel cell (MFC). The maximum power density of MFC with 10% Co/N-C air-cathode is as high as 2514±59mWm(-2), which is almost 174% higher than the control. The exchange current density (i0) of cathode equipped with 10% Co/N-C is 238% higher than that of untreated AC. While the total resistance of treated samples decreases from 13.017 to 10.255Ω. The intensity ratio of Raman D to G band (ID/IG) decreases from 0.93 (N-C) to 0.73 (Co/N-C), indicating the catalyst forms graphite structure. Both XRD and XPS testify that Co is bonded to N within graphitic sheets and serves as the active sites in ORR. The four-electron pathway of the Co/N-C also plays a crucial role in electrochemical catalytic activity. As a result, it can be expected that the as-synthesized Co/N-C, with extraordinary electro-catalytic performance towards ORR, will be a promising alternative to the state-of-the-art non-precious metal ORR electro-catalysts for electrochemical energy applications.

A molecular pathway for CO2 response in Arabidopsis guard cells.

Increasing carbon dioxide (CO2) levels in the atmosphere have caused global metabolic changes in diverse plant species. CO2 is not only a carbon donor for photosynthesis but also an environmental signal that regulates stomatal movements and thereby controls plant-water relationships and carbon metabolism. However, the mechanism underlying CO2 sensing in stomatal guard cells remains unclear. Here we report characterization of Arabidopsis RESISTANT TO HIGH CO2 (RHC1), a MATE-type transporter that links elevated CO2 concentration to repression of HT1, a protein kinase that negatively regulates CO2-induced stomatal closing. We also show that HT1 phosphorylates and inactivates OST1, a kinase which is essential for the activation of the SLAC1 anion channel and stomatal closing. Combining genetic, biochemical and electrophysiological evidence, we reconstituted the molecular relay from CO2 to SLAC1 activation, thus establishing a core pathway for CO2 signalling in plant guard cells.

A DTX/MATE-type transporter facilitates abscisic acid efflux and modulates ABA sensitivity and drought tolerance in Arabidopsis.

Abscisic acid (ABA) regulates numerous physiological and developmental processes in plants. Recent studies identify intracellular ABA receptors, implicating the transport of ABA across cell membranes as crucial for ABA sensing and response. Here, we report that a DTX/Multidrug and Toxic Compound Extrusion (MATE) family member in Arabidopsis thaliana, AtDTX50, functions as an ABA efflux transporter. When expressed heterologously in both an Escherichia coli strain and Xenopus oocyte cells, AtDTX50 was found to facilitate ABA efflux. Furthermore, dtx50 mutant mesophyll cells preloaded with ABA released less ABA compared with the wild-type (WT). The AtDTX50 gene was expressed mainly in the vascular tissues and guard cells and its expression was strongly up-regulated by exogenous ABA. The AtDTX50::GFP fusion protein was localized predominantly to the plasma membrane. The dtx50 mutant plants were observed to be more sensitive to ABA in growth inhibition. In addition, compared with the WT, dtx50 mutant plants were more tolerant to drought with lower stomatal conductance, consistent with its function as an ABA efflux carrier in guard cells.