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Nuclear factor erythroid 2-related factor 2 (Nrf2) is an important transcriptional regulator that plays a protective role against various cardiovascular diseases. Omaveloxolone is a newly discovered potent activator of Nrf2 that has a variety of cytoprotective functions. However, the potential role of omaveloxolone in the process of pathological cardiac hypertrophy and heart failure are still unknown. In this study, an isoproterenol (ISO)-induced pathological cardiac hypertrophy model was established to investigate the protective effect of omaveloxolone in vivo and in vitro. Our study first confirmed that omaveloxolone administration improved ISO-induced pathological cardiac hypertrophy in mice and neonatal cardiomyocytes. Omaveloxolone administration also diminished ISO-induced cardiac oxidative stress, inflammation and cardiomyocyte apoptosis. In addition, omaveloxolone administration activated the Nrf2 signaling pathway, and Nrf2 knockdown almost completely abolished the cardioprotective effect of omaveloxolone, indicated that the cardioprotective effect of omaveloxolone was directly related to the activation of the Nrf2 signaling. In summary, our study identified that omaveloxolone may be a promising therapeutic agent to mitigate pathological cardiac hypertrophy. [ABSTRACT FROM AUTHOR]

The crane & shuttle-based storage and retrieval system (C&SBS/RS) is the first automated warehouse technology that supports pallet picking, case picking and item picking. In the C&SBS/RS, aisle-captive cranes perform pallet picking, while tier-captive shuttles handle cases and items picking. To balance picking tasks, we propose an order dividing algorithm to fulfil required specific picking sequences. The optimisation objective is to minimise the order line picking time. Therefore, we modelled and analyzed the C&SBS/RS and considered single and dual command cycles for each resource (i.e. cranes, rail-guided vehicles, shuttles and lifters) separately according to their respective operation processes. Finally, numerical experiments were conducted to analyze impact factors and a real case to verify the power of the proposed order dividing algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we propose a nonconcave penalized M-estimation of the least absolute relative errors (penalized M-LARE) method for a sparse multiplicative regression model, where the dimension of model can increase with the sample size. Under certain appropriate conditions, the consistency and asymptotic normality for the penalized M-LARE estimator are established. Simulations and a real data analysis are in support of our theoretical results and illustrate that the proposed method performs well. [ABSTRACT FROM AUTHOR]

The motion paths of Balanus reticulatus cyprids were similar on all the titanium alloys surfaces. On the parallel grinding surfaces, the temporary attachment duration and the settlement ratio of the cyprids were influenced by the roughness and the composition of the surfaces and correlated positively. The surface roughness could also change the contact area and the numbers of the attachment points of the cyprids in the similar pattern. Consequently, the roughness and the composition of the surfaces regulated the cyprid settlement by the temporary attachment duration. The cross grinding increased the temporary attachment duration but drastically decreased the settlement ratio to 0 compared to the parallel grinding, possibly due to the voids and the drastic decrease of the contact area and the numbers of the attachment points of the cyprids on the cross grinding surface, respectively. The cross grinding therefore significantly reduced the cyprid settlement compared to the parallel grinding. [ABSTRACT FROM AUTHOR]

This paper considers the zone automated order fulfilment systems with a number of zones linked by a main conveyor. Each zone has a number of dispensers and a buffer. Each dispenser holds one type of item and dispenses the items for an order into a buffer before the items are merged to the main conveyor. Due to variability of the mix of item types and number of items for each type in successive orders, idle time or open space on the conveyor can occur if the buffers merge the items to the conveyor sequentially. The idle time prolongs the order fulfilment duration. This paper aims to provide a solution to reduce the idle time or open space by optimising the merging sequences among zones. A model is developed to find merging sequences with minimum order fulfilment time. However, the model is strongly NP-hard. A greedy heuristic-based solution approach is thus developed. Experiment performance shows that the presented solution can reduce the order fulfilment time approximately 5% with both empirical data and simulation data. Moreover, the sensitivity analysis is conducted to measure the effect of the solution under the variation of zone numbers and order structures. Although the idle time reduction can be achieved with any number of zones and order structures, it was most significant in certain range of zone numbers and appropriate order structures. [ABSTRACT FROM AUTHOR]

Multi-tier shuttle warehousing systems are increasingly popular because of their high flexibility and robustness. These systems consist of a multi-tier shuttle sub-system that controls horizontal movement and a lift sub-system that manages vertical movement. The combination of shuttles and lifts undertakes inbound/outbound tasks instead of the stacker crane in conventional automated storage and retrieval systems. Scheduling different devices to reduce expected cycle time is an important concern. Thus, we propose a time sequence mathematical model of task operation on the basis of the movement characteristics of shuttles and lifts. The task scheduling problem between shuttles and lifts is converted into an assembly line parallel job problem by analysing the mathematical model, which generates the scheduling task queue model in the specified time window. In addition, a Pareto optimal based on an elitist non-dominated sorting genetic algorithm is adopted to solve the multi-objective optimisation function in the task scheduling problem. Finally, we illustrate the findings of the study through a practical example. Results show that the optimisation scheduling solution can reduce the total lift idle time and the total shuttle waiting time. Furthermore, it can improve warehousing efficiency and lower operation costs. [ABSTRACT FROM PUBLISHER]

The least product relative error (LPRE) estimator and test statistic to test linear hypotheses of regression parameters in the multiplicative regression model are studied when the number of covariate variables increases with the sample size. Some properties of the LPRE estimator and test statistic are obtained such as consistency, Bahadur presentation, and asymptotic distributions. Furthermore, we extend the LPRE to a more general relative error criterion and provide their statistical properties. Numerical studies including simulations and two real examples show that the proposed estimation performs well. [ABSTRACT FROM AUTHOR]

Autoregressive (AR) models with finite variance errors have been well studied. This paper is concerned with AR models with heavy-tailed errors, which is useful in various scientific research areas. Statistical estimation for AR models with infinite variance errors is very different from those for AR models with finite variance errors. In this paper, we consider a weighted quantile regression for AR models to deal with infinite variance errors. We further propose an induced smoothing method to deal with computational challenges in weighted quantile regression. We show that the difference between weighted quantile regression estimate and its smoothed version is negligible. We further propose a test for linear hypothesis on the regression coefficients. We conduct Monte Carlo simulation study to assess the finite sample performance of the proposed procedures. We illustrate the proposed methodology by an empirical analysis of a real-life data set. [ABSTRACT FROM AUTHOR]