Search

[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]

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]

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]

• 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]

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]

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]

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]