Obesity caused by a high-fat diet (HFD) affects gut microbiota linked to the risk of type-2 diabetes (T2D). This study evaluates live cells and ethanolic extract (SEL) of Lactobacillus sakei Probio65 and Lactobacillus plantarum Probio-093 as natural anti-diabetic compounds. In-vitro anti-diabetic effects were determined based on the inhibition of α-glucosidase and α-amylase enzymes. The SEL of Probio65 and Probio-093 significantly retarded α-glucosidase and α-amylase enzymes (p < 0.05). Live Probio65 and Probio-093 inhibited α-glucosidase and α-amylase, respectively (p < 0.05). In mice fed with a 45% kcal high-fat diet (HFD), the SEL and live cells of both strains reduced body weight significantly compared to HFD control (p < 0.05). Probio-093 also improved blood glucose level compared to control (p < 0.05). The gut microbiota modulatory effects of lactobacilli on HFD-induced diabetic mice were analyzed with qPCR method. The SEL and live cells of both strains reduced phyla Deferribacteres compared to HFD control (p < 0.05). The SEL and live cells of Probio-093 promoted more Actinobacteria (phyla), Bifidobacterium, and Prevotella (genus) compared to control (p < 0.05). Both strains exerted metabolic-modulatory effects, with strain Probio-093 showing more prominent alteration in gut microbiota, substantiating the role of probiotics in gut microbiome modulations and anti-diabetic effect. Both lactobacilli are potential candidates to lessen obesity-linked T2D.

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This paper deals with a problem of selecting profitable orders to accept out of sequentially arriving customers in a custom production company where only one customer is allowed to be held. It is assumed that a cost must be paid to search for orders, that a delay cost would be paid for every order not completed up to its due date, and that when there was no order in the system, the company could engage in sidelines yielding income. The purpose of this paper is twofold: One is to demonstrate that both admission control and pricing control problems for our customer selection problem can be analyzed within an identical framework and the other is to clarify the properties of the optimal decision rules for this particular problem.

This paper addresses an order picking problem in a multi-aisle automated warehouse, in which a single storage/ retrieval (S/R) machine performs storage and retrieval operations. When retrieval requests consist of multiple items and the items are in multiple stock locations, the S/R machine must travel to several storage locations to complete a customer order. The objective is to minimize the total time traveled by the S/R machine to complete the retrieval process of customer orders at the shortest time. First, we formulate the problem as a nonlinear programming model. Then, we propose a heuristic to solve the problem. Finally, we provide numerical experiments to evaluate the performance of the proposed heuristic. The results show that as the number of items in customer order increases, the heuristic shows a better performance by obtaining solutions close to optimal but in very small amount of times.

We consider a discrete-time admission control problem in a company operating in service industries with two classes of customers. For the first class of customers, the company then (1) has an option to accept or reject him/her (admission control), or (2) decides on an offering price (pricing control). The second-class (sideline) customers are only served if no first-class customers are in the system, and this yields the sideline profit. In this paper, we discuss both admission control and pricing control problems within an identical framework, and we examine the properties of the optimal policies to maximize the total expected present discounted net profits. We show that when the sideline profit is large, the optimal policies may not be monotone in the number of first-class customers in the system.