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Temperature stresses affect plant phenotypic diversity. The developmental stability of the inflorescence, required for reproductive success, is tightly regulated by the interplay of genetic and environmental factors. However, the mechanisms underpinning how plant inflorescence architecture responds to temperature are largely unknown. We demonstrate that the barley SEPALLATA MADS-box protein HvMADS1 is responsible for maintaining an unbranched spike architecture at high temperatures, while the loss-of-function mutant forms a branched inflorescence-like structure. HvMADS1 exhibits increased binding to target promoters via A-tract CArG-box motifs, which change conformation with temperature. Target genes for high-temperature-dependent HvMADS1 activation are predominantly associated with inflorescence differentiation and phytohormone signalling. HvMADS1 directly regulates the cytokinin-degrading enzyme HvCKX3 to integrate temperature response and cytokinin homeostasis, which is required to repress meristem cell cycle/division. Our findings reveal a mechanism by which genetic factors direct plant thermomorphogenesis, extending the recognized role of plant MADS-box proteins in floral development.

The shape of an inflorescence varies among cereals, ranging from a highly branched panicle in rice to a much more compact spike in barley (Hordeum vulgare L.) and wheat (Triticum aestivum L.). However, little is known about the molecular basis of cereal inflorescence architecture. We profiled transcriptomes at three developmental stages of the barley main shoot apex — spikelet initiation, floral organ differentiation, and floral organ growth — and compared them with those from vegetative seedling tissue. Transcript analyses identified 3688 genes differentially transcribed between the three meristem stages, with a further 1394 genes preferentially expressed in reproductive compared with vegetative tissue. Co-expression assembly and Gene Ontology analysis classified these 4888 genes into 28 clusters, revealing distinct patterns for genes such as transcription factors, histone modification, and cell-cycle progression specific for each stage of inflorescence development. We also compared expression patterns of VRS (SIX-ROWED SPIKE) genes and auxin-, gibberellic acid- and cytokinin-associated genes between two-rowed and six-rowed barley to describe regulators of lateral spikelet fertility. Our findings reveal barley inflorescence phase-specific gene expression, identify new candidate genes that regulate barley meristem activities and flower development, and provide a new genetic resource for further dissection of the molecular mechanisms of spike development. Keywords: Inflorescence meristem, Transcriptome, Gene expression, Hormones, Barley

In this article, we studied a robust resource constrained flexible project scheduling problem (RRCFPSP), in which the activity duration is an uncertain number and each activity may have multiple alternative execution routes. We represent RRCFPSP by an AND/OR network and propose a mathematical formulation. Moreover, optimal solution can be reached when the duration of each activity takes the maximum value. To employ the heuristic algorithms which specialise in solving continuous problems to solve the considered problem effectively, we develop a novel float weight optimization frame (FWOF). By combining this frame with particle swarm optimization (PSO), gravity search algorithm (GSA) and whale optimization algorithm (WOA), we propose three algorithms FPSO, FGSA and FWOA respectively. Finally, we design a series of numerical experiments, and experimental results show that the FWOF can make traditional certain heuristic algorithms solve the problems we consider effectively and accurately, especially in large-scale cases.

The mesoporous Co/KIT-6 catalysts with 10 wt% Co loading were prepared at different reduction temperatures. The physicochemical properties of the Co/KIT-6 catalysts were characterized by TEM, BET, XRD, XPS, and CO2-TPD, and the effect of reduction temperature on CO2 hydrogenation catalytic performance of Co/KIT-6 catalysts was studied. The results show that reduction temperature has a significant impact on the specific surface area, crystallinity and content of Co0 species, and CO2 adsorption performance of the prepared Co/KIT-6 catalysts. The low reduction temperature is not conduct to the reduction of CoOx, while the high reduction temperature lead to the increase of Co0 species crystallinity and the formation of Co2SiO4 and/or CosbndOsbndSi species which are unfavorable to the form Co0 species. The RT400 catalyst exhibits the highest Co0 species content and the best CO2 adsorption performance. Both the CO2 hydrogenation catalytic activity and CH4 selectivity of the Co/KIT-6 catalysts follow the order: RT400 > RT350 > RT450 > RT500 > RT550, with a small amount of by-product CO. At the reaction temperature of 340 °C, the CO2 reaction rate (CO2 conversion) of the RT400 catalyst can reach 2.98 × 10−5 mol/gcat/s (40%), the CH4 and CO selectivity are 86.7% and 13.3%, respectively.

This paper analyses a type of extension of the resource-constrained project scheduling problem (RCPSP) whose activities have multiple execution lists. This sort of problem is titled resource-constrained project scheduling problem with flexible activity execution lists (abbreviated as RCPSP-FAL). The goal is to minimize makespan and maximize robustness simultaneously to improve the ability of the project to handle emergencies within the design completion time. Six robustness measures are proposed depending on the free slack determined by start time and renewable resource surplus per unit time. Moreover, a bi-objective mixed-integer programming model is developed to solve the considered problem. Besides, a simple data structure, namely selection-tree, is designed to detect available activity execution lists. Two algorithms are proposed, whose names are variant-genetic algorithm (VGA) and variant-simulated-annealing algorithm (VSA), to solve the developed model. Also, an aggregation function is established for assessing the fitness consisting of makespan and robustness. Several computation experiments are designed to evaluate the proposed algorithms and the six robustness measures. Results show the characteristics of different robust measures. Meanwhile, they also show the effectiveness of VSA and VGA, as well as the relations among robustness, makespan, and resource-usage.

Compared to earlier mobile network generations, the 5G system architecture has been significantly enhanced by the introduction of network analytics functionalities and ex- tended capabilities of interacting with third party Application Functions (AFs). Combining these capabilities, new features for Quality of Experience (QoE) estimation can be designed and introduced in next generation networks. It is, however, unclear how 5G networks can collect monitoring data and application metrics, how they correlate to each other, and which techniques can be used in 5G systems for QoE estimation. This paper studies the feasibility of Machine Learning (ML) techniques for QoE estimation and evaluates their performance for a mobile video streaming use-case. A simulator has been implemented with OMNeT++ for generating traces to (i) examine the relevance of features generated from 5G monitoring data and (ii) to study the QoE estimation accuracy (iii) for a variable number of used features. © ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published here, https://doi.org/10.1145/3349611.3355547

Regional disparities in geographical access to hospital care are found throughout China. Understanding variations in the spatial accessibility of hospital care has the potential to provide decision support in healthcare planning. This study examines the hospital system in the Sichuan Province in China, which provides healthcare for more than 80 million people. We examine the impacts of accessibility characterisation via the conventional measurement approach by comparing the results to those derived using a floating catchment area approach. Employing a geographical information system based on population and hospital administrative data, we conducted a provincewide study of the spatial accessibility of hospital care in Sichuan Province, China. A shortest-path analysis and the enhanced two-step floating catchment area (E2SFCA) method were implemented. Substantial differences between these two approaches were found, including a roughly 15% difference in the total number of under-served areas. Generally, spatial accessibility was higher in the eastern regions of Sichuan. More than 5.5 million people were found to have limited access, with large variations across the province. These results indicate that the official method used by policy makers in China may not capture the true nature of spatial accessibility throughout the region. We recommend that the E2SFCA method be implemented for health services research in China, providing decision makers with more accurate information when setting healthcare policies.

Implementing efficient scheduling and dispatching policies is a critical means to gain competitiveness for modern semiconductor manufacturing systems. In contemporary global market, a successful semiconductor manufacturer has to excel in multiple performance indices, consequently qualified scheduling approaches should provide efficient and holistic management of wafer products, information and manufacturing resources and make adaptive decisions based on real-time processing status to reach an overall optimized system performance. To cope with this challenge, a timed extended object-oriented Petri nets (EOPNs) based multiple-objective scheduling and real-time dispatching approach is proposed in this paper. Four performance objectives pursued by semiconductor manufacturers are integrated into a priority-ranking algorithm that serves as the initial scheduling guidance, and then all wafer lots will be dynamically dispatched by the hybrid real-time dispatching control system. A set of simulation experiments validate the proposed multiple-objective scheduling and real-time dispatching algorithm may achieve satisfactory performances.

Semiconductor wafer fabrication system (SWFS) is the most complex and capital-intensive phase in the entire semiconductor manufacturing cycle. With characteristics of re-entrant processing routes, equipment uncertainty, product diversity and improving technologies, great challenges are presented in SWFS's modeling, scheduling and simulation. To implement efficient production control, this paper provides a timed extended object-oriented Petri nets (TEOPNs) approach to performance modeling, real-timed dispatching and simulation of SWFSs. The TEOPNs models are constructed in a hierarchy to accord with the real-world SWFS's organization, and a new type of signal place is added into the TEOPNs to respond the dynamic states of all processing facilities. A novel autonomy and coordination-based real-time dispatching mechanism (A&C-RDM) is developed in this paper, which executes under the support of the TEOPNs-based hybrid real-time dispatching control system (HRDCS). Owning to the ability of gathering dynamic real-time information of all production facilities and WIP products, the HRDCS can make adaptive dispatching decisions according to the local and global real-time processing status. Two sets of key elements of real-time dispatching, i.e. the state thresholds and dispatching rules, are defined in the HRDCS so that the A&C-RDM can integrate different types of dispatching rules. A set of simulation experiments prove the efficiency of the proposed modeling and dispatching algorithm. In summary, the proposed TEOPNs, HRDCS and A&C-RDM form the cornerstones of a real-time dispatching simulation prototype of SWFS, and the work described in this paper carries out an advanced integrated ''modeling-dispatching-simulation'' methodology.

A self-designed new robot system to be employed in the weld inspection of nuclear pipes is introduced in this paper. This robot system can effectively serve as a substitute for a worker who would otherwise be exposed to a hazardous environment. The robot system includes a half clamp as a mounting unit and a half base as circumferential rotation joint. This system can be mounted on a branch pipe at any position. Its arm is designed with six joints for controlling the position and orientation of the ultrasonic probe (USP), which serves as an end-effector. All of these seven joints, which yield seven degrees of freedom (DOF), are driven by stepper motors. The communication between the Industrial Personal Computer (IPC) and Micro Chip Unit (MCU) is based on RS-485, which allows the robot system to be operated and monitored away from a radiative environment and can therefore limit radiation exposure for the operator. Taking the application at different working sites in nuclear power stations into consideration, the design of the system is based on a modular structure, and the substitution of the clamp and base, as well as the adjustment of the size of the arm links are taken into account. Finally, a test unit for the designed robot system is set up, and experiments show that this system could meet the requirements of a real nuclear power station environment.

In this paper we propose an extended object-oriented Petri nets (EOPNs) for effective modeling of large-scale complex re-entrant manufacturing systems (ReMSs). To cope with their complexity because of the re-entrant process route and the mixed production mode, a special type of transition called a main-bus gate (MBG) is introduced, which can cause products to undergo every re-entrant manufacturing stage. A hierarchical approach is also applied to cope with the complexity. As a typical large-scale complex ReMS, the semiconductor wafer fabrication system (SWFS) is taken as an example for demonstrating the proposed EOPNs. A case study is provided to show the modelling procedures, and the resulting model validates that the EOPNs can cope well with the modelling complexity of large-scale complex ReMSs.