Hydrochlorothiazide/Valsartan

The effect of intermittent food restriction (IFR) on the Central Nervous System is unclear, especially when alternated with an obesity-inducing diet (DIO). This study aimed to evaluate key genes involved in energy-regulation imbalance in the hypothalamus after IFR and DIO alternation. Therefore, 45-d-old female Wistar rats were divided into 4 groups: standard control (ST-C), fed with an ad libitum standard diet; DIO control (DIO-C), fed with a DIO in the first and last 15 d of the intervention and a standard diet between the 16th and 45th day; standard restricted (ST-R), fed with a standard diet in the first and last 15 d of the intervention followed by IFR at 50% of the ST-C diet between the 16th and 45th day; and DIO restricted (DIO-R), fed with a DIO in the first and last 15 d of the intervention and subjected to IFR under the same conditions as the ST-R group. At 105 d of age, animals were euthanized, and the hypothalamus was removed for quantitative polymerase chain reaction analysis. The ST-R and DIO-R groups showed higher inhibitor of nuclear factor kappa-B kinase subunit beta (P < 0.001; P = 0.029) and nuclear factor kappa B (P < 0.001; P = 0.029) gene expression when compared with the ST-C group. The same held true for the JNK (P = 0.001; P = 0.003) and PPARα genes (both P < 0.001). Instead, the DIO-R group exhibited higher CCL5 gene expression than the ST-C (P = 0.001) and DIO-C (P < 0.001) groups, whereas all groups had higher SOCS3 gene expression than did the ST-C group. These data together suggest that IFR, whether combined with DIO or not, alters the expression of critical genes involved in energy regulation imbalance in the hypothalamus, which warrants caution and more research, because long-term usage might be hazardous.

In order to navigate safely and effectively with humans in close proximity, robots must be capable of predicting the future motions of humans. This study first consolidates human studies in motion, intention, and preference into a discretized human model that can readily be used in robotics decision making algorithms. Cooperative Markov Decision Process (Co-MDP), a novel framework that improves upon Multiagent MDPs, is then proposed for enabling socially aware robot obstacle avoidance. Utilizing the consolidated and discretized human model, Co-MDP allows the system to (1) approximate rational human behavior and intention, (2) generate socially-aware robotic obstacle avoidance behavior, and (3) remain robust to the uncertainty of human intention and motion variance. Simulations of a human-robot co-populated environment verify Co-MDP as a feasible obstacle avoidance algorithm. In addition, the anthropomorphic behavior of Co-MDP was assessed and confirmed with a human-in-the-loop experiment. Results reveal that participants can not directly differentiate agents that were controlled by human operators from Co-MDP, and the reported confidences of their choices indicates that the predictions from participants were backed by behavioral evidence rather than random guesses. Thus the main contributions for this paper are: consolidating past human studies of rational human behavior and intention into a simple, discretized model; the development of Co-MDP: a robotic decision framework that can utilize this human model and maximize the joint utility between the human and robot; and an experimental design for evaluation of the human acceptance of obstacle avoidance algorithms.