A similarity-based cooperative co-evolutionary algorithm for dynamic interval multi-objective optimization problems

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Dynamic interval multi-objective optimization problems (DI-MOPs) are very common in real-world applications. However, there are few evolutionary algorithms that are suitable for tackling DI-MOPs up to date. A framework of dynamic interval multi-objective cooperative co-evolutionary optimization based on the interval similarity is presented in this paper to handle DI-MOPs. In the framework, a strategy for decomposing decision variables is first proposed, through which all the decision variables are divided into two groups according to the interval similarity between each decision variable and interval parameters. Following that, two sub-populations are utilized to cooperatively optimize decision variables in the two groups. Furthermore, two response strategies, rgb0.00,0.00,0.00i.e., a strategy based on the change intensity and a random mutation strategy, are employed to rapidly track the changing Pareto front of the optimization problem. The proposed algorithm is applied to eight benchmark optimization instances rgb0.00,0.00,0.00as well as a multi-period portfolio selection problem and compared with five state-of-the-art evolutionary algorithms. The experimental results reveal that the proposed algorithm is very competitive on most optimization instances

Cathepsin K Knockout Mitigates High-Fat Diet–Induced Cardiac Hypertrophy and Contractile Dysfunction

The cysteine protease cathepsin K has been implicated in pathogenesis of cardiovascular disease. We hypothesized that ablation of cathepsin K protects against obesity-associated cardiac dysfunction. Wild-type mice fed a high-fat diet exhibited elevated heart weight, enlarged cardiomyocytes, increased left ventricular wall thickness, and decreased fractional shortening. All these changes were reconciled in cathepsin K knockout mice. Cathepsin K knockout partly reversed the impaired cardiomyocyte contractility and dysregulated calcium handling associated with high-fat diet. Additionally, cathepsin K knockout alleviated whole-body glucose intolerance and improved insulin-stimulated Akt phosphorylation in high-fat diet–fed mice. High-fat feeding increased the expression of cardiac hypertrophic proteins and apoptotic markers, which were inhibited by cathepsin K knockout. Furthermore, high-fat feeding resulted in cathepsin K release from lysosomes into the cytoplasm. In H9c2 myoblasts, silencing of cathepsin K inhibited palmitic acid–induced release of cytochrome c from mitochondria and expression of proapoptotic signaling molecules. Collectively, our data indicate that cathepsin K contributes to the development of obesity-associated cardiac hypertrophy and may represent a potential target for the treatment to obesity-associated cardiac anomalies

Spring-IMU Fusion Based Proprioception for Feedback Control of Soft Manipulators

This paper presents a novel framework to realize proprioception and closed-loop control for soft manipulators. Deformations with large elongation and large bending can be precisely predicted using geometry-based sensor signals obtained from the inductive springs and the inertial measurement units (IMUs) with the help of machine learning techniques. Multiple geometric signals are fused into robust pose estimations, and a data-efficient training process is achieved after applying the strategy of sim-to-real transfer. As a result, we can achieve proprioception that is robust to the variation of external loading and has an average error of 0.7% across the workspace on a pneumatic-driven soft manipulator. The realized proprioception on soft manipulator is then contributed to building a sensor-space based algorithm for closed-loop control. A gradient descent solver is developed to drive the end-effector to achieve the required poses by iteratively computing a sequence of reference sensor signals. A conventional controller is employed in the inner loop of our algorithm to update actuators (i.e., the pressures in chambers) for approaching a reference signal in the sensor-space. The systematic function of closed-loop control has been demonstrated in tasks like path following and pick-and-place under different external loads

ISL1 Promotes Pancreatic Islet Cell Proliferation

BACKGROUND: Islet 1 (ISL1), a LIM-homeodomain transcription factor is essential for promoting pancreatic islets proliferation and maintaining endocrine cells survival in embryonic and postnatal pancreatic islets. However, how ISL1 exerts the role in adult islets is, to date, not clear. METHODOLOGY/PRINCIPAL FINDINGS: Our results show that ISL1 expression was up-regulated at the mRNA level both in cultured pancreatic cells undergoing glucose oxidase stimulation as well in type 1 and type 2 diabetes mouse models. The knockdown of ISL1 expression increased the apoptosis level of HIT-T15 pancreatic islet cells. Using HIT-T15 and primary adult islet cells as cell models, we show that ISL1 promoted adult pancreatic islet cell proliferation with increased c-Myc and CyclinD1 transcription, while knockdown of ISL1 increased the proportion of cells in G(1) phase and decreased the proportion of cells in G(2)/M and S phases. Further investigation shows that ISL1 activated both c-Myc and CyclinD1 transcription through direct binding on their promoters. CONCLUSIONS/SIGNIFICANCE: ISL1 promoted adult pancreatic islet cell proliferation and probably by activating c-Myc and CyclinD1 transcription through direct binding on their promoters. Our findings extend the knowledge about the crucial role of ISL1 in maintaining mature islet cells homeostasis. Our results also provide insights into the new regulation relationships between ISL1 and other growth factors

Tailoring evolutionary algorithms to solve the multi-objective location-routing problem for biomass waste collection

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Location-routing problems widely exist in logistics activities. For the biomass waste collection, there is a recognized need for novel models to locate the collection facilities and plan the vehicle routes. So far most location-routing models fall into the cost-driven-only category. However, comprehensive objectives are required in the specific context, such as time-dependent pollution and speed-and load-related emission. Furthermore, location-routing problems are hierarchical by nature, containing the facility location problems (strategic level) and the vehicle routing problems (tactical level). Existing studies in this field usually adopt computational intelligence methods directly without decomposing the problem. This can be inefficient especially when multiple objectives are applied. Motivated by these, we develop a novel multi-objective optimization model for the location-routing problem for biomass waste collection. To solve this model, we explore the way to tailor evolutionary algorithms to the hierarchical structure. We develop adapted versions of two commonly used evolutionary algorithms: the genetic algorithm and the ant colony optimization algorithm. For the genetic algorithm, we divide the population by the strategic level decisions, so that each subpopulation has a fixed location plan, breaking the location-routing problem down into many multi-depot vehicle routing problems. For the ant colony optimization, we use an additional pheromone vector to track the good decisions on the location level, and segregate the pheromones related to different satellite depots to avoid misleading information. Thus, the problem degenerates into vehicle routing problem. Experimental results show that our proposed methods have better performances on the location routing problem for biomass waste collection

Molecular impact of bone morphogenetic protein 7, on lung cancer cells and its clinical significance

The aim of this study was to investigate the expression of bone morphogenetic protein 7 (BMP7), in human pulmonary cancer tissues/cells and to evaluate the cellular impact of bone morphogenetic proteins on pulmonary cancer cells. BMP7 expression was determined in human lung cancer cell lines. The invasiveness and growth of cells transfected with BMP7, in vitro, were evaluated using the in vitro invasion assay and in vitro tumour models. Cellular migration was analysed using wounding assays. BMP7-positive tumours correlated with the absence of bone metastasis (P=0.040). In this analysis, we identified that 4 of 4 small cell lung cancer (SCLC) tissue specimens had no BMP7 expression, which illustrated that BMP7 may have no role in SCLC. BMP7 expression was not correlated with the overall survival time in lung cancer patients. Downregulation of BMP7 expression significantly inhibited the invasiveness of SPC-A1 cells (P0.5 respectively). In conclusion, we have demonstrated that BMP7 has an important role in controlling lung cancer cell motility and invasiveness, without affecting the growth process, cell proliferation and cell apoptosis. A higher BMP7 expression may be an indicator for bone metastasis. The therapeutic role of BMP7 warrants further investigation