Antioxidant activity of white rice,brown rice and germinated brown rice (in vivo and in vitro) and the effects on lipid peroxidation and liver enzymes in hyperlipidaemic rabbits

Antioxidant activity of different rice extract and the effect on the levels of antioxidant enzyme activity, superoxide dismutase (SOD) and glutathione peroxidase (GPx), vitamin E, lipid peroxidation and liver enzymes in hyperlipidaemia rabbits were investigated. Germinated brown rice (GBR) has the highest antioxidant activity compared to white rice (WR) and brown rice (BR). All rice grains increased the activity of SOD and GPx. However, vitamin E levels increased only in the groups that received the BR and GBR diets. The reduction of lipid peroxidation levels and activity of hepatic enzymes (alanine transferase, ALT and aspartate transaminase, AST) were only significantly observed in the GBR group. In conclusion, GBR supplementation has the greatest impact on increasing antioxidant enzyme activity and vitamin E level and on reducing lipid peroxidation in hypercholesterolaemia rabbit, thereby preventing the formation of atherosclerotic plaques. Furthermore, GBR diet can also reduce the level of hepatic enzymes.     

Anticipation by multi-modal association through an artificial mental imagery process

Mental imagery has become a central issue in research laboratories seeking to emulate basic cognitive abilities in artificial agents. In this work, we propose a computational model to produce an anticipatory behaviour by means of a multi-modal off-line hebbian association. Unlike the current state of the art, we propose to apply hebbian learning during an internal sensorimotor simulation, emulating a process of mental imagery. We associate visual and tactile stimuli re-enacted by a long-term predictive simulation chain motivated by covert actions. As a result, we obtain a neural network which provides a robot with a mechanism to produce a visually conditioned obstacle avoidance behaviour. We developed our system in a physical Pioneer 3-DX robot and realised two experiments. In the first experiment we test our model on one individual navigating in two different mazes. In the second experiment we assess the robustness of the model by testing in a single environment five individuals trained under different conditions. We believe that our work offers an underpinning mechanism in cognitive robotics for the study of motor control strategies based on internal simulations. These strategies can be seen analogous to the mental imagery process known in humans, opening thus interesting pathways to the construction of upper-level grounded cognitive abilities.     

Real-Time Frequency Estimation of Complex GMSK Signal of Green Communications Devices

Parameter estimation of signals of universal software radio peripheral (USRP) devices is crucial to solve the problem of phase offsets of received signals in distributed beamforming. For systems that will utilize the closed loop feedback algorithm where the receiver needs to send the received signal strength (RSS) values periodically to the beamforming node so as to take advantage of energy conservation, the frequency and phase of these signals should be estimated before smoothening by nonlinear filters. This article presents the estimation of the frequency offsets of a Gaussian minimum shift keying (GMSK) signal from N210 USRP devices in real time by using the Radix-2 fast Fourier transform (FFT) algorithm in GNURadio. For these green communications devices, most of the needed hardware parts have been software defined, thereby reducing the supposed energy consumption. The frequency offsets from reference carrier frequencies of 900 MHz and 2.4 GHz are less than 3 kHz each before the estimation, but the average offsets are 45 Hz and 100 Hz after the estimation, respectively. The high offset value experienced with the 2.4 GHz carrier was due to consistent interference from devices on that same frequency.     

Floating content for probabilistic information sharing

People are increasingly using online social networks for maintaining contact with friends and colleagues irrespective of their physical location. While such services are essential to overcome distances, using infrastructure services for location-based services may not be desirable. In contrast, we design and analyze a fully distributed variant of an ephemeral content sharing service, solely dependent on the mobile devices in the vicinity using principles of opportunistic networking. The result is a best effort service for floating content in which content is created locally, its availability is geographically limited and its lifetime and spreading depends on interested nodes being available. In this paper, we present our system design, algorithms, and protocol specification in detail. A set of real world experiments is then used to assess the achievable transmission rates and transmission ranges in such a system. We validate our previous analytical results and assess the performance of floating content in general and especially of different replication and deletion strategies by means of extensive simulations using a map-based mobility model in downtown Helsinki.     

Eleutherine bulbosa (Mill.) Urb. Bulb: Review of the Pharmacological Activities and Its Prospects for Application

Natural product is an excellent candidate for alternative medicine for disease management. The bulb of E. bulbosa is one of the notable Iridaceae family with a variety therapeutic potential that is widely cultivated in Southeast Asia. The bulb has been used traditionally among the Dayak community as a folk medicine to treat several diseases like diabetes, breast cancer, nasal congestion, and fertility problems. The bulb is exceptionally rich in phytochemicals like phenolic and flavonoid derivatives, naphthalene, anthraquinone, and naphthoquinone. The electronic database was searched using various keywords, i.e., E. bulbosa, E. americana, E. palmifolia, E. platifolia, and others due to the interchangeably used scientific names of different countries. Scientific investigations revealed that various pharmacological activities were recorded from the bulb of E. bulbosa including anti-cancer, anti-diabetic, anti-bacterial, anti-fungi, anti-viral, anti-inflammatory, dermatological problems, anti-oxidant, and anti-fertility. The potential application of the bulb in the food industry and in animal nutrition was also discussed to demonstrate its great versatility. This is a compact study and is the first study to review the extensive pharmacological activities of the E. bulbosa bulb and its potential applications. The development of innovative food and pharma products from the bulb of E. bulbosa is of great interest.     

Neuro–fuzzy modelling of spectroscopic data. Part B – Dye concentration prediction

An adaptive network–based fuzzy inference system, ANFIS, has been used for predicting dye concentrations using spectroscopic absorbance data in the visible region. The samples were two–component red/yellow dye solutions with a concentration range of 0–900 mg/l for the one component (red) while the concentration of the other component (yellow) was kept constant. The modelled system had two inputs (wavelength and absorbance) with the concentration values as output. Generalised bell–shaped membership functions were used for the inputs. The inference system used was a first–order Sugeno fuzzy model. The ANFIS models gave concentration prediction results with approximately the same standard error of prediction as artificial neural network (ANN) models. However, the ANFIS model building runs faster than in the case of ANN.     

Comparison of model-based flow rate estimation methods in frequency-converter-driven pumps and fans

Fluid handling systems such as pump and fan systems are found to have a significant potential for energy efficiency improvements. To determine the energy-saving potential, there is a need for easily implementable methods to monitor the system output. This essential information provides an opportunity to identify inefficient operation of the fluid handling system and to control the output of the pumping system according to process needs. Model-based pump or fan monitoring methods implemented in variable-speed drives have proven to be able to give information on the system output without additional metering; however, the present model-based methods may not be usable or sufficiently accurate in the whole operation range of the fluid handling device. To apply model-based system monitoring in a wider selection of systems and to improve the accuracy of the monitoring, this paper proposes a new method for pump and fan output monitoring with variable-speed drives. The method uses a combination of already known operating point estimation methods. Laboratory measurements are used to verify the benefits and applicability of the improved estimation method, and the new method is compared with five previously introduced model-based estimation methods. According to the laboratory measurements, the new estimation method is the most accurate and reliable of the model-based estimation methods.