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Disassembly is an essential step in a remanufacturing process via which valuable parts and material of end-of-life (EOL) products can be well reused and resource waste is reduced. Disassembly sequence planning focuses on finding the best disassembly sequence for a given EOL product by considering economic and environmental performance. In a practical disassembly process, one may face a disassembly operation failure risk due to the difficulty of knowing EOL products’ exact information in advance. Despite its importance in impacting disassembly outcomes, the existing work fails to consider it comprehensively. This work proposes a stochastic biobjective DSP problem with the objectives of maximizing disassembly profit and minimizing energy consumption by doing so. A chance-constrained programming model is established, where a chance constraint ensures a fixed confidence level of disassembly failure. To solve it efficiently, a multiobjective multiverse optimization algorithm with stochastic simulation is proposed. Experiments are carried out on four products. Results demonstrate that it outperforms some state-of-the-art algorithms in terms of solution performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • Reconstituted meat-based products from minced fish exhibited some fibrousness. • Reconstituted fish steaks were prepared via different physical extrusion strength. • Appropriate physical extrusion endowed anisotropic reconstitution during frying. • Porosity and cross-linking network of multi-layered structure were characterized. • Low random coil and moisture content were found in nice multi-layered products. Multi-layered structure of reconstituted meat-based products from minced fish was formed by physical extrusion, followed by an investigation into the impact of extrusion strength on structural and physicochemical properties before and after frying. Under an appropriate pressure (3–9 kPa), the air within minced fish underwent enrichment and rearrangement to form a stratified phase, promoting the formation of multi-layered structure during frying. Conversely, the lower pressure (≤1.5 kPa) was insufficient for phase separation and directional rearrangement, while the higher pressure (≥15 kPa) would cause the stratified phase to flow out of food system. Moreover, by directly increasing water mobility and meat compactness, physical extrusion indirectly caused more water loss and stronger ionic bonds during frying, which was positively correlated with multi-layered structure. However, an excessive pressure caused an increase in random coil and hydrophobic interactions during frying, which was negatively correlated with multi-layered structure. In conclusion, appropriate physical extrusion strength promoted the formation of multi-layered structure. [ABSTRACT FROM AUTHOR]

Remanufacturing attains much attention from both industrial and academic sectors due to its beneficial roles in energy conservation and environment protection, where disassembly is a crucial part. To reach the comprehensive sustainability and global optimization of disassembling multiple end-of-life products, this paper suggests a multi-objective multi-product disassembly line balancing problem with considering disassembly profit, energy consumption and noise pollution simultaneously. According to the natures of the problem under consideration, a multi-objective integer programming model is constructed. Its goals are to reach maximum disassembly profit and realize minimum energy consumption while observing noise pollution requirements and resource constraints. Accordingly, a multi-objective group teaching optimization algorithm is specially devised. In it, rank and crowding distance methods are employed to partition the population into two groups. Moreover, precedence preserving crossover and mutation methods are severally used on the two groups to realize the teacher phase. Furthermore, to achieve the student phase, an adaptive local search method is applied to refine solutions in an external archive, and thus its exploitation ability is enhanced. By executing contrast experiments between the devised approach and its powerful competitors on a set of real-world test instances, the experimental results validate that it has highly-adaptive and well-superior performance in tackling the problem of concern. [Display omitted] [ABSTRACT FROM AUTHOR]

Transition metal-free electrochemical approaches for the N-cyanation of secondary amines and the α C-cyanation of tertiary amines have been well established, with products being obtained in moderate to good yields and with good functional group tolerance under ambient conditions. The synthetic application of the protocols has been highlighted through scale-up experiments in a galvanostatic mode. Preliminary mechanistic investigation has confirmed that TBAB played a critical role in N-cyanation transformation and has indicated that the transformation might proceed via a free radical process. [ABSTRACT FROM AUTHOR]

Hybrid flow shop scheduling problems have gained an increasing attention in recent years because of its wide applications in real-world production systems. Most of the prior studies assume that the processing time of jobs is deterministic and constant. In practice, jobs’ processing time is usually difficult to be exactly known in advance and can be influenced by many factors, e.g., machines’ abrasion and jobs’ feature, thereby leading to their uncertain and variable processing time. In this paper, a dual-objective stochastic hybrid flow shop deteriorating scheduling problem is presented with the goal to minimize makespan and total tardiness. In the formulated problem, the normal processing time of jobs follows a known stochastic distribution, and their actual processing time is a linear function of their start time. In order to solve it effectively, this paper develops a hybrid multiobjective optimization algorithm that maintains two populations executing the global search in the whole solution space and the local search in promising regions, respectively. An information sharing mechanism and resource allocating method are designed to enhance its exploration and exploitation ability. The simulation experiments are carried out on a set of instances, and several classical algorithms are chosen as its peers for comparison. The results demonstrate that the proposed algorithm has a great advantage in dealing with the investigated problem. [ABSTRACT FROM AUTHOR]

Due to its importance in integrating facilities and smoothing supply chain, facility location and capacity planning problem (FLCPP) is no doubt a key issue in constructing an efficient logistics and transportation network. One Belt and One Road (OBOR) initiative aims at reconstructing the logistics and transportation network along the trade corridors and improving the trade connectivity among the developing and developed countries. Nevertheless, under the OBOR initiative, FLCPP is greatly influenced by the government policy for regional development and the uncertain demand incurred by the enormous difference of economic form, custom and culture awareness among the involved countries. This study focuses on a special FLCPP under the OBOR initiative, in which the uncertainties of both policy preference and customer demand are considered simultaneously. To cope with these two categories of uncertainties, this study proposes a simulation-based optimization approach that includes the rough simulation and fine simulation methods. The former aims at finding a set of feasible decisions by using fuzzy and stochastic simulation, while the latter is used to achieve the best decision from the obtained feasible decisions by hybridizing the stochastic simulation with optimal computing budget allocation and mathematical programming. In order to demonstrate the application and advantage of the proposed approach, simulation experiments are conducted and experimental results show that this approach performs well in dealing with the concerned problem as well as some managerial insights and policy suggestions are obtained according to the analysis and results. [ABSTRACT FROM AUTHOR]

Recently, the solution algorithm for multiobjective scheduling problems has gained more and more concerns from the community of operational research since many real-world scheduling problems usually involve multiple objectives. In this paper, a new evolutionary multiobjective optimization (EMO) algorithm, which is termed as decomposition based multiobjective genetic algorithm with adaptive multipopulation strategy (DMOGA-AMP), is proposed to addressmultiobjective permutation flowshop scheduling problems (PFSPs). In the proposed DMOGA-AMP algorithm, a subproblem decomposition scheme is employed to decompose a multiobjective PFSP into a number of scalar optimization subproblems and then introduce the decomposed subproblems into the running course of algorithm in an adaptive fashion, while a subpopulation construction method is employed to construct multiple subpopulations adaptively to optimize their corresponding subproblems in parallel. In addition, several special strategies on genetic operations, i.e., selection, crossover, mutation and elitism, are also designed to improve the performance of DMOGA-AMP for the investigated problem. Based on a set of test instances of multiobjective PFSP, experiments are carried out to investigate the performance of DMOGA-AMP in comparison with several state-of-the-art EMO algorithms. The experimental results show the better performance of the proposed DMOGA-AMP algorithm in multiobjective flowshop scheduling. [ABSTRACT FROM AUTHOR]

Distributed manufacturing scheduling problems have attracted much concern from both industrial and academic areas. Nevertheless, distributed scheduling problems with distribution operations are seldom studied. This work proposes a distributed flexible job shop scheduling problem with distribution operations. A set of jobs is handled at distributed flexible job shops, and then the finished jobs are transported to their corresponding customers following given due dates. First, a mixed integer programming model is established to minimize total tardiness. Second, an ensemble of brain storm optimization and Q-learning methods is developed to solve the formulated model. Six heuristics are hybridized to generate a high-quality initial population. A Q-learning method is devised by fully employing found search information to guide subsequent search processes instead of using fixed parameters as basic brain storm optimization. A variable neighborhood search method combining problem-specific knowledge is designed to further refine the found best individual. At last, the formulated model and method are compared with three state-of-the-art metaheuristics and a mathematical programming solver CPLEX via using a group of problem instances. The results and analysis demonstrate that the developed model and algorithm have more powerful competitiveness in addressing the studied problem. [ABSTRACT FROM AUTHOR]

Recent years have seen a great deal of attention in energy conservation for production and manufacturing activities, particularly for energy-intensive industries. One of the useful strategies in reducing unnecessary energy consumption is to schedule these activities by considering both energy-driven and time-oriented criteria. This scheduling model can make an interaction between the energy consumption and the production cost to realize an efficient and sustainable production process. In this regard, the customers' expectation for due date is another important factor for decision-makers to control the delay in delivery. Making these decisions is extremely difficult due to uncertain circumstances to extract the accurate information of facilities and jobs in advance. Aforementioned issues in the context of urgent need for energy-conservation as well as the advent of globalized and multi-factory manufacture motivate our attempts to address a stochastic multi-objective distributed permutation flow shop scheduling problem by considering total tardiness constraint via minimizing the makespan and the total energy consumption. Due to the uncertainty of the proposed problem, a chance-constrain approach is used to describe decision-makers' awareness for the total tardiness, and accordingly, a chance-constrained programming model is utilized to formulate this problem. As a complicated optimization problem, a new multi-objective brain storm optimization algorithm incorporating stochastic simulation approach is specifically designed to better solve problem. A comparative study based on a set of benchmark test problems as well as two classical and popular algorithms is provided. The experimental results demonstrate that the proposed algorithm shows a very competitive performance in dealing with the investigated problem. [ABSTRACT FROM AUTHOR]

Scheduling problems with resource allocation have received much attention in the academic and industrial communities in recent years. This study addresses a parallel‐machine scheduling problem with resource allocation under the objective of minimizing the makespan, where jobs need an additional resource that is allocated to machines in advance. The processing time of jobs is a function of the amount of allocated resources on their corresponding machines. In order to deal with this problem, three decisions must be made, i.e. resource allocation among machines, job assignment on machines, and job sequence on each machine. To solve this problem efficiently, a constructive heuristic approach and a hybrid nested partition method are designed to make these three decisions. Simulation experiments are carried out on a set of instances, and two existing algorithms are chosen to be compared with the proposed algorithms. Experimental results show that the proposed algorithms are promising in coping with this problem. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Scheduling problems with resource allocation have become of increasing interest in the academic and industrial areas in recent years. This study investigates parallel machine scheduling with dynamic resource allocation under the objective of minimizing the makespan, where the processing of jobs needs an additional resource that can be assigned and reassigned among all jobs, and the processing time of jobs is a function of the amount of allocated resources. Four decisions must be made in a schedule, namely job assignment, job sequence, resource allocation and jobs' starting time. In order to solve it efficiently, a master–slave genetic algorithm is proposed to determine the decisions of job assignment, job sequence and resource allocation, and a greedy heuristic rule is designed to determine the jobs' starting time. To examine the performance of the proposed algorithm, simulation experiments are carried out on a set of instances, and similar existing algorithms and the standard genetic algorithm are chosen as for comparison. The experimental results show that the proposed algorithm is a promising optimizer in solving the investigated problem. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In this paper, a new multi-objective evolutionary algorithm (MOEA) named hybrid MOEA with adaptive multi-population strategy (HMOEA-AMP) is proposed for multi-objective optimization problems (MOPs).In the framework of HMOEA-AMP, the particle swarm optimization and differential evolution are hybridized to guide the exploitation of the Pareto optimal solutions and the exploration of the optimal distribution of the achieved solutions, respectively. Multiple subpopulations are constructed in an adaptive fashion according to a number of scalar subproblems, which are decomposed from a MOP through a set of predefined weight vectors. Comprehensive experiments using a set of benchmark are conducted to investigate the performance of HMOEA-AMP in comparison with several state-of-the-art MOEAs. The experimental results show the advantage of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In recent years, along with our country cadmium pollution in rice is increasingly serious, the safety and quality of rice in China has been under serious threat. Contamination of rice with cadmium also draws great attention because of its serious threat to food safety and its potential harm to human health. Thus, it's very important and necessary for food industry to find a method to decrease the degree of cadmium pollution in polished rice. Cadmium in rice has been demonstrated that it mainly bonded with protein and little cadmium accumulated in starch and other nutritional ingredients. And processing of soaking, heating, washing can reduce the content of cadmium in rice powder, but the effect of cadmium removal is not obvious. Hence, it also was proved that the amount of heavy metals in rice dropped significantly after fermentation using lactic acid bacteria. Therefore, in order to resolve the problem of "excessive cadmium" polished rice utilization, this paper tried to reduce the content of cadmium in "excessive cadmium" polished rice(cadmium content of 0.6479mg/kg) by lactic acid bacteria and produce safe fermented rice products, and the fermentation conditions were studied and optimized. The mixed strains of Lactobacillus plantarum and Pediococcus pentosaceus(2:1,v/v) were selected as the suitable fermentation strain by comparative test. The effects of rice powder size, fermentation time, fermentation temperature and inoculum size of mixed strains on the removal rate of cadmium in polished rice also were evaluated by single-factor experiment. The results showed that fermentation time, fermentation temperature and inoculum size of mixed strains could significantly affect the removal rate of cadmium(P<0.05). However, the effect of rice powder size(20-100 mesh) on the removal rate of cadmium was not significant(P>0.05). Then, fermentation time, fermentation temperature and inoculum size of mixed strains were further researched using a three-variable, three level Box-Benhnken design to optimize the fermentation conditions. The results indicated that the interaction effects of fermentation temperature and fermentation time, fermentation temperature and inoculum size of mixed strains on the removal rate of cadmium were extremely significant (P<0.01). Moreover, the significant degree of three factors was in order as fermentation temperature (A, P<0.01)>fermentation time (B, P<0.01)>inoculum size of mixed strains (C, P<0.01). When rice powder size was selected as 40 mesh, the optimum fermentation conditions were obtained with fermentation temperature of 40.8, fermentation time of 23.4 h, and the inoculum size of 3%. In this optimal conditions, the verification test demonstrated that the removal rate of cadmium in polished rice powder was 85.73%, and the content of cadmium in fermented rice noodle was 0.0925 mg/kg and met the national food sanitation standard (0.2 mg/kg). In addition, the verification test showed that there was a good fit between the experimental and the predicted values, relative standard deviation was 0.918. Therefore, the results indicated that this method could efficiently remove cadmium in polished rice and provide a reference for industrial production of fermented rice noodle. The results of research also can provide a theoretical basis for further study on the mechanism on cadmium removal in rice by lactic acid bacteria. [ABSTRACT FROM AUTHOR]

[Objective] The research aimed to analyze characteristics of atmospheric electric field in polluted area. [Method] By using data of atmospheric electric field meter in Taiyuan in 2009, daily and annual changes of atmospheric electric field in Taiyuan were analyzed. [Result] Atmospheric electric field intensity in Taiyuan was higher than that in other areas. Daily change was double-peak double-valley type. The first highest value appeared at nightfall, and the second highest value was before the noon. The first lowest value appeared in early morning, while the second lowest value appeared after the noon. Annual change was single-peak single-valley type. The maximum appeared in winter, while the minimum appeared in summer. [Conclusion] When forecasting thunderstorm, in the area with higher aerosol content, alarm threshold of electric field should be adjusted via comparison with actual observation, which had very strong regional characteristics. By analyzing real-time monitoring data of atmospheric electric field, thunderstorm forecast could be realized, and timeliness and accuracy of warning and forecast could be increased. [ABSTRACT FROM AUTHOR]

• This work studies an integrated distributed flow shop scheduling and distribution problem. • A mixed integer programming model is given to describe this problem mathematically. • An enhanced brain storm optimization algorithm is designed. • Optimal solutions are obtained by using mathematical programming solvers. • State-of-the-art results are acquired by the designed approach. Production and distribution are two essential activities in supply chain management. Currently, integrated production and distribution problems receive much attention because decision-makers devote to improving the operation efficiency of both stages and try to achieve an optimal solution. This work proposes an integrated distributed production and distribution problem with consideration of time windows, in which a set of jobs (i.e., customer orders) needs to be assigned among factories and the jobs are processed on flow shop environments at their associated factories. Then, the completed jobs are delivered by capacitated vehicles to customers in different regions while satisfying given time windows as much as possible. Accordingly, to optimally solve the proposed problem, a mixed integer programming model with minimizing total weighted earliness and tardiness has been established. For the optimization task, an enhanced brain storm optimization algorithm with some particular strategies is designed to handle the considered problem. To assess the performance of the proposed optimization method, several experiments by adopting a set of benchmark test problems are performed, and state-of-the-art optimizers are chosen for comparisons. The obtained optimization results exhibit that the designed algorithm significantly outperforms its rivals and can be considered as an excellent optimizer for solving the studied problem. Besides, compared with the CPLEX solver, the designed optimizer also performs much better for solving large-size problems. [ABSTRACT FROM AUTHOR]

Community Supported Agriculture (CSA), which offers two outstanding advantages, high-quality food and localized production, has come to the fore. In CSA, the output of picking scheduling is the input of delivery scheduling. Hence, only by scheduling the picking stage and distribution stage in a coordinated way can we achieve fresh agricultural products at minimum cost. However, due to asymmetric information in the picking and distribution stage, the integrated scheduling of picking and distribution may lead to an asymmetric optimization problem, which is suitable for solving with an iterative algorithm. Based on this, this work studies an integrated scheduling problem of the picking and distribution of fresh agricultural products with the consideration of minimizing picking and distribution costs as well as maximizing the freshness of orders. First, a nonlinear mixed-integer programming model for the problem under consideration is constructed. Second, a multi-objective multi-population genetic algorithm with local search (MOPGA-LS) is designed. Finally, the algorithm is compared with three multi-objective optimization algorithms in the literature: the non-dominated sorted genetic algorithm-II (NSGA-Ⅱ), the multi-objective evolutionary algorithm based on decomposition (MOEA/D), and the multi-objective evolutionary algorithm based on decomposition that is combined with the bee algorithm (MOEA/D-BA). The comparison results show the excellent performance of the designed algorithm. Thus, the reported model and algorithm can assist managers and engineers in making well-informed decisions in managing the farm operation. [ABSTRACT FROM AUTHOR]

A new selectable marker system was adapted for use in Agrobacterium-mediated transformation of rice (Oryza sativa L.). This selection system utilizes the pmi gene encoding for phosphomannose-isomerase that converts mannose-6-phosphate to fructose-6-phosphate. Only transformed cells were capable of utilizing mannose as a carbon source. Transgenic rice plants regenerated from selected transformed immature embryo-derived calli on media containing various concentrations of mannose. The highest transformation frequency of 6.0% was obtained when a combination of 25 g/l mannose and 5 g/l sucrose was used. Molecular and genetic analyses showed that the plants contained the pmi gene and the gene was transmitted to the progeny in Mendelian fashion. The results indicated that the mannose selection system, which was devoid of the disadvantages of antibiotic or herbicide selection, could be used for rice Agrobacterium-mediated immature embryo transformation. [Copyright &y& Elsevier]

Remanufacturing end-of-life (EOL) products is an important approach to yield great economic and environmental benefits. A remanufacturing process usually contains three shops, i.e., disassembly, processing and assembly shops. EOL products are dissembled into multiple components in a disassembly shop. Reusable components are reprocessed in a processing shop, and reassembled into their corresponding products in an assembly shop. To realize an overall optimization, we have to integrate them together when making decisions. In practice, a decision-maker usually has to optimize multiple criteria such as cost-related and service-oriented objectives. Additionally, we cannot accurately acquire the detail of EOL products due to their various usage processes. Therefore, multi-objective and uncertainty need to be considered simultaneously in an integrated disassembly-reprocessing-reassembly scheduling process. This work investigates a stochastic multi-objective integrated disassembly-reprocessing-reassembly scheduling problem to achieve the expected makespan and total tardiness minimization. To handle this problem, this work develops a multi-objective discrete fruit fly optimization algorithm incorporating a stochastic simulation approach. Its search techniques are designed according to this problem's features from five aspects, i.e., solution representation, heuristic decoding rules, smell-searching, vision-searching, and genetic-searching. Simulation experiments are conducted by adopting twenty-five instances to verify the performance of the proposed approach. Nondominated sorting genetic algorithm II, bi-objective multi-start simulated annealing method, and hybrid multi-objective discrete artificial bee colony are chosen for comparisons. By analyzing the results with three performance metrics, we can find that the proposed approach performs better on all the twenty-five instances than its peers. Specifically, it outperforms them by 6.45%–9.82%, 6.91%–17.64% and 1.19%–2.76% in terms of performance, respectively. The results confirm that the proposed approach can effectively and efficiently tackle the investigated problem. [ABSTRACT FROM AUTHOR]

Ene reductases (ERs) are attractive biocatalysts in terms of their high enantioselectivity and expanded substrate scope. Recent works have proved that synthetic nicotinamide coenzyme biomimetics (NCBs) can be used as easily accessible alternatives to natural cofactors in ER‐catalyzed reactions. However, the structure‐reactivity relationships between NCBs and ERs and influence factors are still poorly understood. In this study, a series of C‐5 methyl modified NCBs were synthesized and tested in the PETNR‐catalyzed asymmetric reductions. The physicochemical properties of these NCBs including electrochemical properties, stability, and kinetic behavior were studied in detail. The results showed that hydrophobic interaction caused by the introduced methyl group contributed to the stabilization of binding conformation in enzyme active site, resulting in comparable catalytic activity with that of NADPH. Molecular dynamics and steered molecular dynamics simulations were further performed to explain the binding mechanism between PETNR and NCBs, which revealed that stable catalytic conformation, appropriate donor‐acceptor distance and angle, as well as free dissociation energy are important factors affecting the activity of NCBs. [ABSTRACT FROM AUTHOR]

In recent years, the global resource shortage has become a serious issue. Recycling end-of-life (EOL) products is conducive to resource reuse and circular economy and can mitigate the resource shortage issue. The disassembly of EOL products is the first step for resource reuse. Disassembly activities need tools, and tool deterioration occurs inevitably during the disassembly process. This work studies the influence of tool deterioration on disassembly efficiency. A disassembly line balancing model with the goal of maximizing disassembly profits is established, in which tool selection and assignment is a critical part. A modified discrete migratory bird optimizer is proposed to solve optimization problems. The well-known IBM CPLEX optimizer is used to verify the correctness of the model. Six real-world products are used for disassembly experiments. The popular fruit fly optimization algorithm, whale optimization algorithm and salp swarm algorithm are used for search performance comparison. The results show that the discrete migratory bird optimizer outperforms all three other algorithms in all disassembly instances. [ABSTRACT FROM AUTHOR]

Summary: Grain yield is one of the most important and complex trait for genetic improvement in crops; it is known to be controlled by a number of genes known as quantitative trait loci (QTLs). In the past decade, many yield‐contributing QTLs have been identified in crops. However, it remains unclear whether those QTLs confer the same yield performance in different genetic backgrounds. Here, we performed CRISPR/Cas9‐mediated QTL editing in five widely‐cultivated rice varieties and revealed that the same QTL can have diverse, even opposing, effects on grain yield in different genetic backgrounds. [ABSTRACT FROM AUTHOR]

The theoretical research on the percolation mechanism and oil-water relative permeability of low-permeability oil reservoirs is the focus and hotspot of international researchers. Oil-water relative permeability is an important parameter that describes the characteristics of oil-water two-phase flow and is widely used in the dynamic analysis of development and numerical simulation technology in the reservoir. The traditional calculation method of oil-water relative permeability (i.e., the JBN method) is based on the Darcy flow law. When the velocity and the displacement pressure gradient do not follow the linear flow law, there are some errors in the results of oil-water relative permeability calculated by the JBN method. In this paper, the traditional JBN method is improved, and we establish a new processing method of experimental data for oil-water relative permeability considering the effects of nonlinear flow, capillary pressure, and gravity in tight oil reservoirs. The experiments on the flow characteristics of single-phase oil and oil-water relative permeability under nonsteady-state conditions were carried out. The flow velocity and displacement pressure gradient show nonlinear characteristics when single-phase oil is passed through a tight core. At the same time, when the air permeability decreases from 1.92 × 10 − 3 μ m 2 to 0.1 × 10 − 3 μ m 2 , the nonlinear characteristics are becoming more and more obvious. Compared with the traditional JBN method, when the nonlinear flow characteristics are considered, the oil phase relative permeability increases, and the water phase relative permeability is slightly lower. If nonlinear flow characteristics are considered, when the water saturation increases from 0.605 to 0.699, the difference of oil phase relative permeability calculated by the JBN method and this method is gradually decreasing and, with the increase of water saturation, decreases from 0.0029 to 0.0001. In addition, the effects of capillary pressure, gravity, and the nonlinear flow coefficient on the oil-water relative permeability in tight oil reservoirs are studied. The capillary pressure also has a great influence on the relative permeability of the oil phase, and the relative permeability of the oil phase increases with the increase in capillary pressure. In the development process of the low-permeability reservoir, the seepage characteristics of each flow area are different, and the oil-water relative permeability is also different. Therefore, the research results play an important role in guiding the understanding of seepage characteristics of low permeability of tight oil reservoirs. [ABSTRACT FROM AUTHOR]

ABSTRACT The BURP-domain protein family comprises a diverse group of plant-specific proteins that share a conserved BURP domain at the C terminus. However, there have been only limited studies on the functions and subcellular localization of these proteins. Members of the RD22-like subfamily are postulated to associate with stress responses due to the stress-inducible nature of some RD22-like genes. In this report, we used different transgenic systems (cells and in planta) to show that the expression of a stress-inducible RD22-like protein from soybean (GmRD22) can alleviate salinity and osmotic stress. We also performed detailed microscopic studies using both fusion proteins and immuno-electron microscopic techniques to demonstrate the apoplast localization of GmRD22, for which the BURP domain is a critical determinant of the subcellular localization. The apoplastic GmRD22 interacts with a cell wall peroxidase and the ectopic expression of GmRD22 in both transgenic Arabidopsis thaliana and transgenic rice resulted in increased lignin production when subjected to salinity stress. It is possible that GmRD22 regulates cell wall peroxidases and hence strengthens cell wall integrity under such stress conditions. [ABSTRACT FROM AUTHOR]

The articel offers information on the expanding the range of CRISPR/Cas9 genome editing in rice using using the VQR and VRER Cas9 Variants.

Abstract: Auxin response factors (ARFs) are transcription factors that bind with specificity to TGTCTC-containing auxin response elements (AuxREs) found in promoters of primary/early auxin response genes and mediate responses to the plant hormone auxin. The ARF genes are represented by a large multigene family in plants. A comprehensive genome-wide analysis was carried out in this study to find all ARFs in Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa subsp. japonica), 23 and 25 ARF genes, named as AtARFs and OsARFs, were identified, respectively. Chromosomal locations of all OsARFs were presented and it was found that the duplication of OsARFs was associated with only the chromosomal block duplications but not local tandem duplications. A phylogenetic tree was generated from alignments of the full-length protein sequences of 25 OsARFs and 23 AtARFs to examine the phylogenetic relationships of rice and Arabidopsis ARF proteins. All 48 members of ARF gene families fell into three major classes, a total of 13 sister pairs, including 9 OsARF–OsARF, 2 AtARF–AtARF and 2 AtARF–OsARF sister pairs were formed, showing different orthologous relationships between AtARFs and OsARFs. EST analysis and RT-PCR assays demonstrated that 24 of all 25 OsARF genes were active and the transcript abundance of some OsARF genes was affected by auxin treatment or light- and dark-grown conditions. The outcome of the present study provides basic genomic information for the rice ARF gene family and will pave the way for elucidating the precise role of OsARFs in plant growth and development in the future. [Copyright &y& Elsevier]

Small fructans improve plant tolerance for cold stress. However, the underlying molecular mechanisms are poorly understood. Here, we have demonstrated that the small fructan tetrasaccharide nystose improves the cold stress tolerance of primary rice roots. Roots developed from seeds soaked in nystose showed lower browning rate, higher root activity, and faster growth compared to seeds soaked in water under chilling stress. Comparative proteomics analysis of nystose-treated and control roots identified a total of 497 differentially expressed proteins. GO classification and KEGG pathway analysis documented that some of the upregulated differentially expressed proteins were implicated in the regulation of serine/threonine protein phosphatase activity, abscisic acid-activated signaling, removal of superoxide radicals, and the response to oxidative stress and defense responses. Western blot analysis indicated that nystose promotes the growth of primary rice roots by increasing the level of RSOsPR10, and the cold stress-induced change in RSOsPR10levelis regulated by jasmonate, salicylic acid, and abscisic acid signaling pathways in rice roots. Furthermore, OsMKK4-dependentmitogen-activated protein kinase signaling cascades may be involved in the nystose-induced cold tolerance of primary rice roots. Together, these results indicate that nystose acts as an immunostimulator of the response to cold stress by multiple signaling pathways. [ABSTRACT FROM AUTHOR]

Experimental design focuses on describing or explaining the multifactorial interactions that are hypothesized to reflect the variation. The design introduces conditions that may directly affect the variation, where particular conditions are purposely selected for observation. Combinatorial design theory deals with the existence, construction and properties of systems of finite sets whose arrangements satisfy generalized concepts of balance and/or symmetry. In this work, borrowing the concept of “balance” in combinatorial design theory, a novel method for multifactorial bio-chemical experiments design is proposed, where balanced templates in combinational design are used to select the conditions for observation. Balanced experimental data that covers all the influencing factors of experiments can be obtianed for further processing, such as training set for machine learning models. Finally, a software based on the proposed method is developed for designing experiments with covering influencing factors a certain number of times. [ABSTRACT FROM AUTHOR]

Flowering time is an important agronomic trait that coordinates the plant life cycle with regional adaptability and thereby impacts yield potentials for cereal crops. The CONSTANS ( CO )-like gene family plays vital roles in the regulation of flowering time. CO-like proteins are typically divided into four phylogenetic groups in rice. Several genes from groups I, III, and IV have been functionally characterized, though little is known about the genes of group II in rice. We report the functional characterization in rice of a constitutive floral inhibitor, OsCOL16 , encoding a group-II CO-like protein that delays flowering time and increases plant height and grain yield. Overexpression of OsCOL16 resulted in late heading under both long-day and short-day conditions. OsCOL16 expression exhibits a diurnal oscillation and serves as a transcription factor with transcriptional activation activity. We determined that OsCOL16 up-regulates the expression of the floral repressor Ghd7 , leading to down-regulation of the expression of Ehd1 , Hd3a , and RFT1 . Moreover, genetic diversity and evolutionary analyses suggest that remarkable differences in flowering times correlate with two major alleles of OsCOL16 . Our combined molecular biology and phylogeographic analyses revealed that OsCOL16 plays an important role in regulating rice photoperiodic flowering, allowing for environmental adaptation of rice. [ABSTRACT FROM AUTHOR]

A rice mutant with light-green leaves was discovered from a transgenic line of Oryza sativa . The mutant has reduced chlorophyll content and abnormal chloroplast morphology throughout its life cycle. Genetic analysis revealed that a single nuclear-encoded recessive gene is responsible for the mutation, here designated as lgl1. To isolate the lgl1 gene, a high-resolution physical map of the chromosomal region around the lgl1 gene was made using a mapping population consisting of 1984 mutant individuals. The lgl1 gene was mapped in the 76.5 kb region between marker YG4 and marker YG5 on chromosome 12. Sequence analysis revealed that there was a 39 bp deletion within the fourth exon of the candidate gene Os12g0420200 (TIGR locus Os12g23180) encoding a chloroplast stem-loop-binding protein of 41 kDa b (CSP41b). The lgl1 mutation was rescued by transformation with the wild type CSP41b gene. Accordingly, the CSP41b gene is identified as the LGL1 gene. CSP41b was transcribed in various tissues and was mainly expressed in leaves. Expression of CSP41b-GFP fusion protein indicated that CSP41b is localized in chloroplasts. The expression levels of some key genes involved in chlorophyll biosynthesis and photosynthesis, such as ChlD , ChlI , Hema1 , Ygl1 , POR , Cab1R , Cab2R , PsaA , and rbcL , was significantly changed in the lgl1 mutant. Our results demonstrate that CSP41b is a novel gene required for normal leaf color and chloroplast morphology in rice. [ABSTRACT FROM AUTHOR]

The article discusses a study which shows that the genetic combination frequency could be increased by partial mutation of the gene using rice as a model crop. Topics discussed include the importance of plant fertility for genetic analysis, observation that the truncated ZEP1 protein can form discrete foci and short stretches in 95% of meiocytes and findings that partial loss of function of the rice Synaptonemal Complex (SC) reduces the strength of genetic interference.

Rice hull, the outer cover of the rice grain, determines grain shape and size. Changes in the rice hull proteome in different growth stages may reflect the underlying mechanisms involved in grain development. To better understand these changes, isobaric tags for relative and absolute quantitative (iTRAQ) MS/MS was used to detect statistically significant changes in the rice hull proteome in the booting, flowering, and milk-ripe growth stages. Differentially expressed proteins were analyzed to predict their potential functions during development. Gene ontology (GO) terms and pathways were used to evaluate the biological mechanisms involved in rice hull at the three growth stages. In total, 5,268 proteins were detected and characterized, of which 563 were differentially expressed across the development stages. The results showed that the flowering and milk-ripe stage proteomes were more similar to each other (r=0.61) than either was to the booting stage proteome. A GO enrichment analysis of the differentially expressed proteins was used to predict their roles during rice hull development. The potential functions of 25 significantly differentially expressed proteins were used to evaluate their possible roles at various growth stages. Among these proteins, an unannotated protein (Q7X8A1) was found to be overexpressed especially in the flowering stage, while a putative uncharacterized protein (B8BF94) and an aldehyde dehydrogenase (Q9FPK6) were overexpressed only in the milk-ripe stage. Pathways regulated by differentially expressed proteins were also analyzed. Magnesium-protoporphyrin IX monomethyl ester [oxidative] cyclase (Q9SDJ2), and two magnesium-chelatase subunits, ChlD (Q6ATS0), and ChlI (Q53RM0), were associated with chlorophyll biosynthesis at different developmental stages. The expression of Q9SDJ2 in the flowering and milk-ripe stages was validated by qRT-PCR. The 25 candidate proteins may be pivotal markers for controlling rice hull development at various growth stages and chlorophyll biosynthesis pathway related proteins, especially magnesium-protoporphyrin IX monomethyl ester [oxidative] cyclase (Q9SDJ2), may provide new insights into the molecular mechanisms of rice hull development and chlorophyll associated regulation. [ABSTRACT FROM AUTHOR]

A narrow leaf mutant was isolated from transgenic rice ( Oryza sativa L.) lines carrying a T-DNA insertion. The mutant is characterized by narrow leaves during its whole growth period, and was named nal9 ( narrow leaf 9). The mutant also has other phenotypes, such as light green leaves at the seedling stage, reduced plant height, a small panicle and increased tillering. Genetic analysis revealed that the mutation is controlled by a single recessive gene. A hygromycin resistance assay showed that the mutation was not caused by T-DNA insertion, so a map-based cloning strategy was employed to isolate the nal9 gene. The mutant individuals from the F2 generations of a cross between the nal9 mutant and Longtepu were used for mapping. With 24 F2 mutants, the nal9 gene was preliminarily mapped near the marker RM156 on the chromosome 3. New INDEL markers were then designed based on the sequence differences between japonica and indica at the region near RM156. The nal9 gene was finally located in a 69.3 kb region between the markers V239B and V239G within BAC OJ1212_C05 by chromosome walking. Sequence and expression analysis showed that an ATP-dependent Clp protease proteolytic subunit gene ( ClpP) was most likely to be the nal9 gene. Furthermore, the nal9 mutation was rescued by transformation of the ClpP cDNA driven by the 35S promoter. Accordingly, the ClpP gene was identified as the NAL9 gene. Our results provide a basis for functional studies of NAL9 in future work. [ABSTRACT FROM AUTHOR]

The article analysis involvement of nutrition response and root growth(NRR) gene in rice heading date regulation. It mentions that NRR is spliced in two segments namely NRRa and NRRb which regulate negatively growth of root in rice plants under the macronutrient-deficient conditions. It discusses differences between NRRa and NRRb genes and discusses role of these genes in regulating flowering in rice. It has been found that overexpression of the gene NRRa results in delayed in heading date.

Small silencing RNAs (sRNAs) are non-coding RNA regulators that negatively regulate gene expression by guiding mRNA degradation, translation repression or chromatin modification. Plant sRNAs play crucial roles in various developmental processes, hormone signaling, immune responses and adaptation to a variety of abiotic stresses. miR441 and miR446 were previously annotated as microRNAs (miRNAs) because their precursors can form typical stem-loop structures, but are not considered as real miRNAs because of inconsistency with some ancillary criteria of the recent guidelines for annotation of plant miRNAs. We tentatively rename them small interfering (si)R441 and siR446, respectively, in this study. It has recently been shown that the precursors of siR441 and siR446 might originate from the miniature inverted-repeat transposable element (MITE) Stowaway1. In this report, we show that, in contrast with Dicer-like (DCL)3- and RNA-dependent RNA polymerase (RDR)2-dependent MITE-derived ra-siRNAs, siR441 and siR446 are processed by OsDCL3a but independent of OsRDR2, indicating that siR441 and siR446 are generated from single-stranded stem-loop precursors. We also show that abscisic acid (ABA) and abiotic stresses downregulate the expression of siR441 and siR446 but, surprisingly, increase the accumulation of their precursors in rice plants, implying that processing of siRNA precursors is inhibited. We provide evidence to show that this defective processing is due to increased precursor accumulation per se, possibly by intermolecular self-pairing of the processing intermediate sequences, thus hindering their normal processing. Functional examinations indicate that siR441 and siR446 are positive regulators of rice ABA signaling and tolerance to abiotic stress, possibly by regulating MAIF1 expression. [ABSTRACT FROM AUTHOR]

• G-proteins (guanine nucleotide-binding proteins that usually exhibit GTPase activities) and related signal transduction processes play important roles in mediating plant defense responses; here, a rice ( Oryza sativa) cDNA clone, OsGAP1, encoding a GTPase-activating protein (GAP) that also contains a protein kinase C conserved region 2 (C2) domain is reported. • An interacting G-protein partner for the OsGAP1 protein was identified by yeast two-hybrid library screening and confirmed by co-immunoprecipitation; the GTPase-activation activity of OsGAP1 on this interacting G-protein was demonstrated using in vitro assays. • OsGAP1 was induced by wounding in rice and the presence of the R locus Xa14 enhances such induction. • Gain-of-function tests in transgenic rice and Arabidopsis thaliana showed that constitutive expression of OsGAP1 led to increased resistance to bacterial pathogens in both monocots and dicots. [ABSTRACT FROM AUTHOR]

Presents a genetic analysis and identification of a large leaf angles mutant found in rice. Establishment of a large number of T-DNA insertional rice mutant pools; Isolation of the genes from the rice; Participation of WRKY gene in plant developmental processes.