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Backgrounds: Restless legs syndrome (RLS) is an unpleasant condition that affects the quality of life of patients. Its prevalence in increased in women with premenstrual syndrome (PMS). Vitamin D plays a key role in female reproduction through its impact on calcium homeostasis and neurotransmitters. We aimed to evaluate the effect of dairy products fortified with Vitamin D3 on RLS in women with PMS. Materials and methods: We conducted a 2.5-month, randomized, total-blinded clinical trial to evaluate the effectiveness of low-fat milk and yogurt fortified with vitamin D on RLS in women with PMS. Among 141 middle-aged women with abdominal obesity, 71 and 70 cases received fortified and non-fortified low-fat dairy products, respectively. All subjects completed a Symptoms Screening Tool (PSST) and RLS questionnaires. Results: The results showed that in the women with severe PMS (PSST > 28), serum levels of vitamin D increased significantly following vitamin D fortification. The mean restless legs score in the severe PMS subgroup (PSST > 28) was significantly lower after the intervention (p < 0.05. Serum Vitamin D levels significantly differed between intervention and control groups in all individuals (PSST < 19, PSST 19–28, and PSST > 28) (p < 0.05), but no significant differences were found between RLS scores of the intervention and control groups in the three PMS subgroups (p > 0.05). Conclusion: Fortifying dairy products with vitamin D3 can increase the serum levels of vitamin D and reduce the RLS severity in women with severe PMS, but not in other groups. [ABSTRACT FROM AUTHOR]

This paper presents an iterative approach for solving the optimal control problem (OCP) with time-delayed terms and bounded control variables. The projection function is used to construct the iterative method to approximate the control law. Employing the approximation of control law the approximation of state and the co-state variables are obtained. To the best of our knowledge, this paper is the first attempt to solve bounded and delayed OCPs with a projection function. The convergence theorem for the proposed method is also proven. Several numerical examples are added, showing the developed method's effectiveness to solve the time-delayed OCPs with bounded control variables. [ABSTRACT FROM AUTHOR]

This study assessed the association between atherosclerosis indices, serum uric acid to high‐density lipoprotein cholesterol ratio (UHR) and triglyceride‐glucose (TyG) index and the prevalence of hypertension among MASHAD cohort participants. In this cross‐sectional study, the participants were divided into hypertensive and non‐hypertensive subjects. The atherosclerosis indices, UHR and TyG index of the two groups were compared. Logistic regression analyses were used to determine the associations of these indices with hypertension in both sex. Receiver operating characteristic (ROC) curve analysis was used to establish the cut‐off values for differentiating hypertensive from non‐hypertensive subjects. p‐values <.05 were considered statistically significant. Data related to 9675 subjects (3035 hypertensive and 6640 non‐hypertensive) were analyzed. The mean values of atherosclerosis indices, UHR and TyG index were significantly higher (p <.001) in the hypertensives compared to non‐hypertensives. After adjustment for potential confounders, among men, the TyG index (OR = 1.360; 95% CI: 1.210–1.530; p <.001) remained an independent factor for hypertension. Among women, atherogenic index of plasma (OR = 1.005; 95% CI: 1.002–1.007; p <.001), UHR (OR = 1.043; 95% CI: 1.026–1.060; p <.001) and TyG index (OR = 1.519; 95% CI: 1.376–1.677; p <.001) remained independent factors for hypertension. ROC curve analysis revealed that compare to the other indices, TyG index had a better predictive value for hypertension in both sex, especially in women. [ABSTRACT FROM AUTHOR]

We develop a projection recurrent neural network (RNN) to obtain the solution of the shortest path problem (SPP). Our focus on the paper is to give a compact single-layer structure RNN model to solve the SPP. To present the RNN model, we utilise a mixed linear complementarity problem (MLCP). Moreover, the developed RNN is proved to be globally stable. Finally, some numerical simulations are stated to show the performance of the presented approach. We compare the results with some other methods. [ABSTRACT FROM AUTHOR]

Finished products and manufacturing plants are some elements of the production system in the supply chain, and there are other manufacturing plants. They produce work in process and finished products and hold them in warehouses. So, they need to plan and control production and inventories. Isolated planning and control by different manufacturers increase inventories in them, and then they must plan and control integratory. This paper presents an iterative approach for solving the optimal control problem with bounded control variables. The projection function constructs the iterative method to approximate the control law. Employing the approximation of control law, the approximation of state and the co-state variables are obtained. For this purpose, we apply the Hamiltonian of the optimal control problem. From the Hamiltonian, the approximation of control law and then the approximation of state law is obtained. A simple example is given to compare the results with another published paper. Also, a case study on production planning in a three-stock reverse logistics system with deteriorating items is derived to show the method's performance. [ABSTRACT FROM AUTHOR]

Classic linear assignment method is a multi-criteria decision-making approach in which criteria are weighted and each rank is assigned to a choice. In this study, to abandon the requirement of calculating the weight of criteria and use decision attributes prioritizing and also to be able to assign a rank to more than one choice, a multi-objective linear programming (MOLP) method is suggested. The objective function of MOLP is defined for each attribute and MOLP is solved based on absolute priority and comprehensive criteria methods. For solving the linear programming problems we apply a recurrent neural network (RNN). Indeed, the Lyapunov stability of the proposed model is proved. Results of comparing the proposed method with TOPSIS, VICOR, and MORA methods which are the most common multi-criteria decision schemes show that the proposed approach is more compatible with these methods. [ABSTRACT FROM AUTHOR]