Postural adjustments to self-triggered perturbations under conditions of changes in body orientation

We studied anticipatory and compensatory postural adjustments (APAs and CPAs) associated with self-triggered postural perturbations in conditions with changes in the initial body orientation. In particular, we were testing hypotheses on adjustments in the reciprocal and coactivation commands, role of proximal vs. distal muscles, and correlations between changes in indices of APAs and CPAs. Healthy young participants stood on a board with full support or reduced support area and held a standard load in the extended arms. They released the load in a self-paced manned with a standard small-amplitude arm movement. Electromyograms of 12 muscles were recorded and used to compute reciprocal and coactivation indices between three muscle pairs on both sides of the body. The subject's body was oriented toward one of three targets: straight ahead, 60° to the left, and 60° to the right. Body orientation has stronger effects on proximal muscle pairs compared to distal muscles. It led to more consistent changes in the reciprocal command compared to the coactivation command. Indices of APAs and CPAs showed positive correlations across conditions. We conclude that the earlier suggested hierarchical relations between the reciprocal and coactivation command could be task-specific. Predominance of negative or positive correlations between APA and CPA indices could also be task-specific

Automatic Classification of eruptive events by the VAMOS system

An automatic system named VAMOS (Volcanic Activity MOnitoring System) for monitoring volcanic activity at Mt. Etna and Stromboli volcanoes, is at the present under test at the data collection center at IIV (Istituto Internazionale di Vulcanologia, CNR, Catania). This system allows automatic recognition of volcanic activity by on-line processing of images collected by the surveillance cameras positioned close to the summit crater of two above mentioned volcanoes which are worldwide known to be characterized by a persistent eruptive activity. Based on this automatic system, a new software tool to extract quantitative information from collected images is now under developing. Several tasks have been planned to solve by using this tool such as the automatic classification of recorded events and the computation of relaxed energy based on stereo-vision and thermal images. One of the first result of the undertaken research activity has been the automatic classification of the type of volcanic events and the localization of the eruptive event

Adjusted Light and Dark Cycles Can Optimize Photosynthetic Efficiency in Algae Growing in Photobioreactors

Biofuels from algae are highly interesting as renewable energy sources to replace, at least partially, fossil fuels, but great research efforts are still needed to optimize growth parameters to develop competitive large-scale cultivation systems. One factor with a seminal influence on productivity is light availability. Light energy fully supports algal growth, but it leads to oxidative stress if illumination is in excess. In this work, the influence of light intensity on the growth and lipid productivity of Nannochloropsis salina was investigated in a flat-bed photobioreactor designed to minimize cells self-shading. The influence of various light intensities was studied with both continuous illumination and alternation of light and dark cycles at various frequencies, which mimic illumination variations in a photobioreactor due to mixing. Results show that Nannochloropsis can efficiently exploit even very intense light, provided that dark cycles occur to allow for re-oxidation of the electron transporters of the photosynthetic apparatus. If alternation of light and dark is not optimal, algae undergo radiation damage and photosynthetic productivity is greatly reduced. Our results demonstrate that, in a photobioreactor for the cultivation of algae, optimizing mixing is essential in order to ensure that the algae exploit light energy efficiently

Effect of residence time in continuous photobioreactor on mass and energy balance of microalgal protein production

There is increasing interest in new protein sources for the food and feed industry and for the agricultural sector, and microalgae are considered a good alternative, having a high protein content and a well-balanced amino acid profile. However, protein production from microalgae presents several unsolved issues, as the biomass composition changes markedly as a function of cultivation operating conditions. Continuous systems, however, may be properly set to boost the accumulation of protein in the biomass, ensuring stable production. Here, two microalgae and two cyanobacterial species were cultivated in continuous operating photobioreactors (PBR) under nonlimiting nutrient conditions, to study the effects of light intensity and residence time on both biomass and protein productivity at steady state. Although light strongly affected biomass growth inside the PBR, the overall protein pool did not vary in response to irradiance. On the other hand, shorter residence times resulted in protein accumulation of up to 68 % in cyanobacteria, in contrast with green algae, where a minor influence of residence time on biomass composition was observed. Energy balance showed that light conversion to protein decreased with light intensity. Protein content was also related to energy costs for cell maintenance. In conclusion, it is shown that residence time is the key variable to increase protein content and yield of protein production, but its effect depends on the specific species

Improving cubic EOSs near the critical point by a phase-space cell approximation

Cubic equations of state (EOSs) are widely used to model the thermodynamic properties of pure fluids and mixtures. However, because they fail to account for the long-range fluctuations existing in a fluid near the critical point, they do not accurately predict the fluid properties in the critical region. Recently, an approximate renormalization group method was developed that can account for these fluctuations.A similar method is applied to provide corrections to a generalized cubic EOS for pure fluids, which is able to represent all classic cubic EOSs. The proposed approach requires two additional parameters:<(c)over bar(RG)> and Delta. The value of <(c)over bar(RG)> is correlated to experimental critical compressibility data, while Delta is set equal to 1. The method is applied to predict the saturated liquid density of fluids of different polarity, and the corrections to the original EOS are found to significantly improve the predictions of this property both far from and close to the critical point. Finally,a correlation is presented for the direct evaluation of the parameter<(c)over bar(RG)> from the value of the critical compressibility factor

An internally LED illuminated photobioreactor to increase energy conversion efficiency: Design and operation

In this work, a novel internally LED illuminated prototype photobioreactor (IIPBR) was designed, rationalizing the light supply with a hexagonal geometry and matching the light spectrum to the most photosynthetically active wavelengths. The IIPBR was designed and operated to produce the biomass in a continuous mode. In this system, Acutodesmus obliquus was cultivated under different light intensities (100–400 µmol m−2 s−1) and residence times (1–1.9 d). At steady state, a maximum productivity of 40.09 ± 1.99 g m−2 d-1 and a photosynthetic efficiency around 22 % were obtained. The data collected were used to carry out a first evaluation of the costs related to illumination, finding that the correct setting of the operative conditions has a great impact on costs, which span from a minimum of 1.82 up to to 20.63 € kg−1 (with electricity supply rated at autumn–winter 2021). The photoconversion efficiency of the lamps and the plant location play an important role and should be taken into account to increase the economic feasibility of the system proposed, thus enlarging the possible fields final applications of the biomass obtained

Cellular neural networks for real-time monitoring of volcanic activity

The paper introduces a new methodology for real-time monitoring of active volcanoes, which is based on efficient video processing operations implemented by means of cellular neural network (CNN) architectures. CNNs are massive parallel analog circuits with only local interconnections between the computing elements, that are programmed in an analog way to perform almost all image processing operations. The performance of CNN-based operations is reported by simulation of some dynamic image processing tasks in active volcano monitoring. The purpose of the proposed computer-based system for volcanic image processing is twofold: on-line signalling of volcanic events of interest such as lava fountains, Strombolian explosions, ash and gas emissions, etc., and real-time extraction of quantitative information which characterises the events, i.e. geometric parameters, energy involved, type of event and so on. The performance of the present version of the system is limited, in terms of processing speed, by the simulator instead of the on-chip analog CNN, which is still under development by STMicroelectronics. Hence the system can operate well only when volcanic activity is not paroxysmal. The system has been tested on images taken both on Etna and Stromboli, volcanoes located in southern Italy, but it can easily be adapted in order to work in other volcanic areas. The technique implemented for the image-processing operations, called 'CNN-ADI', was conceived for moving image processing and combines the cumulative differences model with the computational speed and versatility of CNNs, implementing a pseudo-ADI (accumulative difference image) algorithm. The advantage of using a CNN-based version of the ADI filter lies in the possibility of real-time filtering, directly on-chip of short sequences of images to distinguish between the dynamic and static elements the frames contain. The main advantages of the present work are that not only are human operators relieved of the task of visual monitoring but it is also possible to extract on-line physical parameters of volcanic events, including event classification