A multi-objective brain storm optimization for integrated distributed flexible job shop and distribution problems.

Production and distribution are critical components of the furniture supply chain, and achieving optimal performance through their integration has become a vital focus for both the academic and business communities. Moreover, as economic globalization progresses, distributed manufacturing has become a pioneering production technique. Via leveraging a distributed flexible manufacturing system, mass flexible production at lower costs can be achieved. To this end, this study presents an integrated distributed flexible job shop and distribution problem to minimize makespan and total tardiness. In our research, a set of custom furniture orders from different customers are processed among flexible job shops and then delivered by vehicles to customers as the due date. To distinctly show the presented problem, a mixed integer mathematical programming model is created, and a multi-objective brain storm optimization method is introduced considering the problem's features. In comparison to the other three advanced methods, the superiority of the algorithm created is showcased. The findings of the experiments demonstrate that the constructed model and the introduced algorithm have remarkable competitiveness in addressing the problem being examined.

Multi-layered structure and physicochemical properties of reconstituted meat-based products from minced fish by physical extrusion: Impact of extrusion strength.

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.

Improving U-net network for semantic segmentation of corns and weeds during corn seedling stage in field.

Introduction: Weeds are one of the main factors affecting crop growth, making weed control a pressing global problem. In recent years, interest in intelligent mechanical weed-control equipment has been growing. Methods: We propose a semantic segmentation network, RDS_Unet, based on corn seedling fields built upon an improved U-net network. This network accurately recognizes weeds even under complex environmental conditions, facilitating the use of mechanical weeding equipment for reducing weed density. Our research utilized field-grown maize seedlings and accompanying weeds in expansive fields. We integrated the U-net semantic segmentation network, employing ResNeXt-50 for feature extraction in the encoder stage. In the decoder phase, Layer 1 uses deformable convolution with adaptive offsets, replacing traditional convolution. Furthermore, concurrent spatial and channel squeeze and excitation is incorporated after ordinary convolutional layers in Layers 2, 3, and 4. Results: Compared with existing classical semantic segmentation models such as U-net, Pspnet, and DeeplabV3, our model demonstrated superior performance on our specially constructed seedling grass semantic segmentation dataset, CGSSD, during the maize seedling stage. The Q6mean intersection over union (MIoU), precision, and recall of this network are 82.36%, 91.36%, and 89.45%, respectively. Compared to those of the original network, the proposed network achieves improvements of 5.91, 3.50, and 5.49 percentage points in the MIoU, precision, and recall, respectively. The detection speed is 12.6 frames per second. In addition, ablation experiments further confirmed the impactful contribution of each improvement component on the overall semantic segmentation performance. Discussion: This study provides theoretical and technical support for the automated operation of intelligent mechanical weeding devices.

Dual-objective modeling and optimization of a low-carbon waste-classified collection problem.

With improved quality of life, types of waste have become increasingly complex, and waste classification has become a global issue. As a result, the world is facing a waste-classified collection problem. However, the existing research on waste collection has paid little attention to waste classification. In this paper, we consider the pretreatment and classification of waste transfer stations. In recent years, global warming caused by carbon emissions has become a serious problem. Therefore, this work proposes the first dual-objective multi-depot two-echelon green vehicle routing system with various pickups to optimize waste-classified collection based on a mixed-integer programming model. To ensure the efficiency of our developed model, we designed a multiobjective brainstorming optimization algorithm with a novel clustering strategy based on the rank-clustering method and differential mutation. Compared with two classical multiobjective optimization algorithms in various generated test instances and a real-world case, the experimental results showed that the proposed model can help sanitation departments improve the economic and environmental benefits of waste-classified collection, and the proposed algorithm is an excellent optimizer for solving associated problems.

Cooperative chemoenzymatic synthesis of N-heterocycles via synergizing bio- with organocatalysis.

Inspired by Nature's ingenuity, considerable progress has been made in recent years to develop chemoenzymatic processes by the integration of environmentally friendly feature of biocatalysis with versatile reactivity of chemocatalysis. However, the current types of chemoenzymatic processes are relatively few and mostly rely on metal catalysts. Here, we report a previously unexplored cooperative chemoenzymatic system for the synthesis of N-heterocycles. Starting from alcohols and amines, benzimidazole, pyrazine, quinazoline, indole, and quinoline can be obtained in excellent yields in water with O2 as the terminal oxidant. Synthetic bridged flavin analog is served as a bifunctional organocatalyst for the regeneration of cofactor nicotinamide adenine dinucleotide in the bioprocess and oxidative cyclodehydrogenation in the chemoprocess. Compared to the classical acceptorless dehydrogenative coupling strategy, being metal and base free, requiring only water as solvent, and not needing atmosphere protection were observed for the present method, exhibiting a favorable green and sustainable alternative.

A multi-stage supply chain disruption mitigation strategy considering product life cycle during COVID-19.

The global pandemic of COVID-19 has caused severe damage to the supply chain such that manufacturers may face long-term supply disruptions. In this paper, a disruption recovery strategy of a supply chain system is investigated from the perspective of product change, in which the life cycle and design change time of a new product are both considered in order to minimize the losses of manufacturer after disruptions. A mixed-integer linear programming (MILP) model is presented to address the disruption recovery problem for this multi-period, multi-supplier, and multi-stage supply chain system. A two-stage heuristic algorithm is designed to solve the problem. Experimental results show that the proposed disruption mitigation strategy can effectively reduce the profit loss of manufacturer due to supply disruption, and demonstrate the impact of product life cycle in the selection of new product design planning. A sensitivity analysis is performed to ensure the applicability of the model in the actual environment, which illustrates the effect of different parameter changes on the results. This work can help manufacturers establish an optimal recovery strategy whenever the supply chain system experiences supply disruptions.

Modeling and optimization for noise-aversion and energy-awareness disassembly sequence planning problems in reverse supply chain.

Nowadays, the reverse supply chain management receives much attention because of its critical role in environmental protection and economic development. Disassembly is very important in the reverse supply chain. It aims at dismantling valuable components from end-of-life products which are then remanufactured into like-new ones after reprocessing and reassembly operations. To efficiently organize and manage the remanufacturing process from the perspective of sustainable development, this work proposes a stochastic disassembly sequence planning problem with consideration of noise pollution and energy consumption to achieve disassembly profit maximization. A chance-constrained programming model is formulated to describe it mathematically. Then, a discrete marine predators algorithm combined with a stochastic simulation approach is specially designed. By conducting simulation experiments on some real-life instances and comparing the designed approach with two popularly known methods in literature, we mainly find that the proposed model and approach can make better disassembly plan for the investigated problem with maximal profit subject to the given noise pollution and energy consumption constraints. The results demonstrate that the proposed method can efficiently and effectively handle the considered problem, which contributes to reaching the highly reliable and environmentally sustainable disassembly process.

Nystose regulates the response of rice roots to cold stress via multiple signaling pathways: A comparative proteomics analysis.

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.

p33ING1b regulates acetylation of p53 in oral squamous cell carcinoma via SIR2.

BACKGROUND: Oral squamous cell carcinoma (OSCC), a form of head and neck squamous cell carcinoma (HNSCC) has a poor 5-year survival rate. OSCC patients are often treated with cisplatin but resistance to chemotherapy is often observed. This makes it important identification of alternative therapeutic targets which will result in more favorable outcome in OSCC patients. The plant homeodomain (PHD)-containing protein Inhibitor of Growth family of tumor suppressor proteins (p33ING1b) has been indicated as a tumor suppressor in different cancers including OSCC. This protein has been shown to function by modulating transcriptional activity of p53; however, the exact mechanism(s) are not well defined. METHODS: Expression of total and acetylated p53 and p33ING1b protein was determined in OSCC cell lines YD-9, YD-8, and YD-38 by immunoblot analysis. Effect of modulation of p33ING1b protein expression on acetylation of p53 and cell proliferation was determined by immunoblot and MTT assay. Effect of modulation of p33ING1b protein expression on transactivation of p53 was assessed by heterologous promoter-based reporter and chromatin immunoprecipitation. Effect of modulation of expression of p33ING1b on SIR2 mRNA and protein was determined by quantitative real-time PCR and immunoblot analyses. Impact of modulation of p33ING1b alone or in combination with SIR2 on chemosensitivity of YD-9 and YD-8 cells to cisplatin was determined in time and dose-dependent cell proliferation assays. RESULTS: Here, using a panel of OSCC cell lines with wild type or mutant p53, we show that p33ING1b expression is correlated to acetylation of p53 at lysine 382 residue. Increased acetylation of p53 following overexpression of p33ING1b was associated with increased expression of the pro-apoptotic proteins BAX, p21, and cleaved-Caspase 3, and decreased cell proliferation. Reporter assays with p21 and BAX promoters showed that p33ING1b expression levels directly correlated to promoter activity of these 2 genes. Chromatin immunoprecipitation assay showed that transcriptional regulation of p21 and BAX by acetylated p53 is dependent on expression level of p33ING1b. Differential acetylation of p53 following modulation of p33ING1b expression was indirect. Expression of p33ING1b was found to be inversely correlated to the NAD-dependent deacetylase silent information regulator 2 (SIR2). SIR2 was transcriptionally regulated by p33ING1b. Relative expression of p33ING1b was found to dictate chemosensitivity of OSCC cell lines to cisplatin treatment. Concomitant overexpression of p33ING1b and knockdown of SIR2 had a synergistic effect on chemosensitivity of OSCC cell lines to cisplatin, compared to either overexpression of p33ING1b or knockdown of SIR2 alone. CONCLUSIONS: The results from the current study thus elucidate that p33ING1b regulates p53 acetylation irrespective of p53 mutation and subsequent transactivation by transcriptional regulation of SIR2 expression. The results also indicate that p33ING1b and SIR2 are potentially attractive therapeutic targets.

Downregulation of nuclear ING3 expression and translocalization to cytoplasm promotes tumorigenesis and progression in head and neck squamous cell carcinoma (HNSCC).

ING3 (inhibitor of growth gene 3) is a member of the ING gene family, and is considered as a candidate tumor suppressor gene. In order to explore the roles of ING3 in tumorigenesis and cancer progression of head and neck squamous cell carcinoma (HNSCC), ING3 expression was assessed in 173 cases of HNSCC by immunohistochemistry. The expression of ING3 was also compared to clinicopathological variables, and the expression of several tumorigenic markers. Nuclear expression of ING3 in HNSCC was significantly lower than that in dysplasia and normal epithelium, and was negatively correlated with a poor-differentiated status, T staging and TNM staging. In contrast, cytoplasmic expression of ING3 was significantly increased in HNSCC, and was statistically associated with lymph node metastasis and 14-3-3η expression. In addition, nuclear expression of ING3 was positively correlated with the expression of p300, p21 and acetylated p53. In conclusion, decreases in nuclear ING3 may play important roles in tumorigenesis, progression and tumor differentiation in HNSCC. Increases in cytoplasmic ING3 may be due to 14-3-3η binding and may also be involved in malignant progression. Nuclear ING3 may modulate the transactivation of target genes, promoting apoptosis through interactions with p300 and p21. Moreover, ING3 may interact with p300 to upregulate the level of acetylation of p53, and promote p53-mediated cell cycle arrest, senescence and/or apoptosis. Therefore, ING3 may be a potential tumor suppressor and a possible therapeutic target in HNSCC.