A project scheduling approach to production planning with feeding precedence relations

In Manufacturing-to-Order or Engineering-to-Order systems producing complex and highly customised items, each item has its own characteristics that are often tailored for a specific customer. Project scheduling approaches are suitable for production planning in such environments. However, when we consider the production of complex items, the distinct production operations are often aggregated into activities representing whole production phases. In such cases, the planning and scheduling problem works on the aggregate activities, considering that, in most cases, such activities also have to be manually executed. Moreover, simple finish-to-start precedence relations no longer correctly represent the real production process, but overlapping among activities should be allowed. In this paper, a project scheduling approach is proposed for production planning in Manufacturing-to-Order systems. The Variable Intensity formulation is used to allow the effort committed to the execution of activities to vary over time. Feeding precedences are developed to model generalised precedence relations when the execution mode of activities is not known a priori. Two mathematical formulations of these precedence relations are proposed. The formulations are applied both to randomly generated instances and to an industrial system producing machining centres and are compared in terms of computational efficiency.     

A Pareto biogeography-based optimisation for multi-objective two-sided assembly line sequencing problems with a learning effect

This research presents a Pareto biogeography-based optimisation (BBO) approach to mixed-model sequencing problems on a two-sided assembly line where a learning effect is also taken into consideration. Three objectives which typically conflict with each other are optimised simultaneously comprising minimising the variance of production rate, minimising the total utility work and minimising the total sequence-dependent setup time. In order to enhance the exploration and exploitation capabilities of the algorithm, an adaptive mechanism is embedded into the structure of the original BBO, called the adaptive BBO algorithm (A-BBO). A-BBO monitors a progressive convergence metric in every certain generation and then based on this data it will decide whether to adjust its adaptive parameters to be used in the next certain generations or not. The results demonstrate that A-BBO outperforms all comparative algorithms in terms of solution quality with indifferent solution diversification.     

Pre-Analytical Considerations for Successful Next-Generation Sequencing (NGS): Challenges and Opportunities for Formalin-Fixed and Paraffin-Embedded Tumor Tissue (FFPE) Samples

In cancer drug discovery, it is important to investigate the genetic determinants of response or resistance to cancer therapy as well as factors that contribute to adverse events in the course of clinical trials. Despite the emergence of new technologies and the ability to measure more diverse analytes (e.g., circulating tumor cell (CTC), circulating tumor DNA (ctDNA), etc.), tumor tissue is still the most common and reliable source for biomarker investigation. Because of its worldwide use and ability to preserve samples for many decades at ambient temperature, formalin-fixed, paraffin-embedded tumor tissue (FFPE) is likely to be the preferred choice for tissue preservation in clinical practice for the foreseeable future. Multiple analyses are routinely performed on the same FFPE samples (such as Immunohistochemistry (IHC), in situ hybridization, RNAseq, DNAseq, TILseq, Methyl-Seq, etc.). Thus, specimen prioritization and optimization of the isolation of analytes is critical to ensure successful completion of each assay. FFPE is notorious for producing suboptimal DNA quality and low DNA yield. However, commercial vendors tend to request higher DNA sample mass than what is actually required for downstream assays, which restricts the breadth of biomarker work that can be performed. We evaluated multiple genomics service laboratories to assess the current state of NGS pre-analytical processing of FFPE. Significant differences in pre-analytical capabilities were observed. Key aspects are highlighted and recommendations are made to improve the current practice in translational research.     

Initial pH influences microbial communities composition in dark fermentation of scotta permeate

This study addresses for the first time the influence of initial pH on the evolution of microbial consortia in dark fermentation of scotta permeate, using a high-throughput sequencing approach. Three fermentation phases could be detected: 1) a lag phase with no substantial differences in microbial composition at different initial pH values; 2) an exponential H₂ production phase, accompanied by a general increase of Clostridium genus components and higher incidence of Trichococcus genus at neutral and alkaline pH; 3) a final stationary phase, characterized by a general increase of Bifidobacterium and Lactobacillus genera in all reactors. The initial pH value influenced the relative abundance of Trichococcus at 16–48 h of incubation. The metabolic activity of this genus increased the amount of metabolic precursors of H₂ so that, when pH lowered to 5.4, clostridia in the reactors with initial alkaline pH become more active H₂-producers than those in the others.     

Molecular identification of honey entomological origin based on bee mitochondrial 16S rRNA and COI gene sequences

The increasing recognition and production of stingless bee honey has raised the needs to develop rapid, sensitive and accurate methodologies for honey identification through bees' species from the DNA of bees present in honey. Genetic identification of raw honeys produced by different bee species from Malaysia was performed based on mitochondrial DNA sequences and phylogenetic analysis by means of forensically informative nucleotide sequencing (FINS) technique. The 300 bp of mitochondrial large subunit ribosomal RNA (16S rRNA) gene region and mitochondrial cytochrome c oxidase subunit I (COI) gene region were the gene markers used to classify and identify honey produced by Apis honey bees and Trigona stingless bees. The genetic identities of honey origin from Apis dorsata, Apis mellifera, Apis cerana, and Heterotrigona itama were accurately identified. Kelulut honey sourced from the stingless bee was distinguishable from other Apis type of honeys in phylogenetic analyses. This FINS technique is a specific and reliable method for identification of honey origin via its bee source that can be used to overcome the issue of false declaration of honey origin and mislabelling.     

污水厂SBR池DO变化过程及研究

对污水厂SBR池曝气及后搅拌过程中的DO变化情况进行连续监测,取其中5个周期的数据进行分析,并考察曝气时序DO、p H与氮转化的相关性,计算SBR系统的OUR及SOUR值。结果显示曝气过程DO变化可分为3个阶段:第1阶段DO接近1.97 mg/L,波动较大;第2阶段DO稳定上升;第3阶段DO进入平台期。DO与混合液中有机物浓度负相关,有可能通过DO间接表示混合液中有机物浓度。DO和p H可以联合起来指示硝化过程的终点。     

Isolation and Characterization of a Glycosyl Hydrolase Family 16 β-Agarase from a Mangrove Soil Metagenomic Library

A mangrove soil metagenomic library was constructed and a β-agarase gene designated as AgaML was isolated by functional screening. The gene encoded for a 659-amino-acids polypeptide with an estimated molecular mass of 71.6 kDa. The deduced polypeptide sequences of AgaML showed the highest identity of 73% with the glycoside hydrolase family 16 β-agarase from Microbulbifer agarilyticus in the GenBank database. AgaML was cloned and highly expressed in Escherichia coli BL21(DE3). The purified recombinant protein, AgaML, showed optimal activity at 50 °C and pH 7.0. The kinetic parameters of K_m and V_max values toward agarose were 4.6 mg·mL⁻¹ and 967.5 μM·min⁻¹·mg⁻¹, respectively. AgaML hydrolyzed the β-1,4-glycosidic linkages of agar to generate neoagarotetraose (NA4) and neoagarohexaose (NA6) as the main products. These characteristics suggest that AgaML has potential application in cosmetic, pharmaceuticals and food industries.