Mapping the research on aquaculture. A bibliometric analysis of aquaculture literature

Research on aquaculture is expanding along with the exceptional growth of the sector and has an important role in supporting even further the future developments of this relatively young food production industry. In this paper we examined the aquaculture literature using bibliometrics and computational semantics methods (latent semantic analysis, topic model and co-citation analysis) to identify the main themes and trends in research. We analysed bibliographic information and abstracts of 14,308 scientific articles on aquaculture recorded in Scopus. Both the latent semantic analysis and the topic model indicate that the broad themes of research on aquaculture are related to genetics and reproduction, growth and physiology, farming systems and environment, nutrition, water quality, and health. The topic model gives an estimate of the relevance of these research themes by single articles, authors, research institutions, species and time. With the co-citation analysis it was possible to identify more specific research fronts, which are attracting high number of co-citations by the scientific community. The largest research fronts are related to probiotics, benthic sediments, genomics, integrated aquaculture and water treatment. In terms of temporal evolution, some research fronts such as probiotics, genomics, sea-lice, and environmental impacts from cage aquaculture, are still expanding while others, such as mangroves and shrimp farming, benthic sediments, are gradually losing weight. While bibliometric methods do not necessarily provide a measure of output or impact of research activities, they proved useful for mapping a research area, identifying the relevance of themes in the scientific literature and understanding how research fronts evolve and interact. By using different methodological approaches the study is taking advantage of the strengths of each method in mapping the research on aquaculture and showing in the meantime possible limitations and some directions for further improvements.     

Electronic nose and sensorial analysis: comparison of performances in selected cases

Sensorial analysis based on the utilisation of human senses, is one of the most important and straightforward investigation methods in food analysis. It provides a unique information about the ‘food–man interaction’. Nevertheless, human senses, when considered as instruments, show several problems of reproducibility, stability and difficulties of expression, making it very hard to compare results between different panels. The electronic nose has been proven to be sufficiently accurate as an artificial approximation of the human olfaction apparatus when applied to well defined problems in food analysis. In this paper results obtained for tomato pastes and milk analysis, comparing a panel of tasters and an electronic nose will be presented and discussed.     

Predicting categorical forest variables using an improved k-Nearest Neighbour estimator and Landsat imagery

The k-Nearest Neighbour (k-NN) estimation and prediction technique is widely used to produce pixel-level predictions and areal estimates of continuous forest variables such as area and volume, often by sub-categories such as species. An advantage of k-NN is that the same parameters (e.g., k-value, distance metric, weight vector for the feature space variables) can be used for all variables, whether continuous or categorical. An obvious question is the degree to which accuracy can be improved if the k-NN estimation parameters are tailored for specific variable groups such as volumes by tree species or categorical variables. We investigated prediction of categorical forest attribute variables from satellite image spectral data using k-NN with optimisation of the weight vector for the ancillary variables obtained using a genetic algorithm. We tested several genetic algorithm fitness functions, all derived from well-known accuracy measures. For a Finnish test site, the categorical forest attribute variables were site fertility and tree species dominance, and for an Italian test site, the variables were forest type and conifer/broad-leaved dominance. The results for both test sites were validated using independent data sets. Our results indicate that use of the genetic algorithm to optimize the weight vector for prediction of a single forest attribute variable had a slight positive effect on the prediction accuracies for other variables. Errors can be further decreased if the optimisation is done by variable groups.     

Self-Assembling Peptides: From Design to Biomedical Applications

Self-assembling peptides could be considered a novel class of agents able to harvest an array of micro/nanostructures that are highly attractive in the biomedical field. By modifying their amino acid composition, it is possible to mime several biological functions; when assembled in micro/nanostructures, they can be used for a variety of purposes such as tissue regeneration and engineering or drug delivery to improve drug release and/or stability and to reduce side effects. Other significant advantages of self-assembled peptides involve their biocompatibility and their ability to efficiently target molecular recognition sites. Due to their intrinsic characteristics, self-assembled peptide micro/nanostructures are capable to load both hydrophobic and hydrophilic drugs, and they are suitable to achieve a triggered drug delivery at disease sites by inserting in their structure’s stimuli-responsive moieties. The focus of this review was to summarize the most recent and significant studies on self-assembled peptides with an emphasis on their application in the biomedical field.     

A wireless multimedia framework for the management of emergency situations in automotive applications: The AIDER system

Automotive applications would greatly benefit of multimedia telematic services for many purposes, from tourism and entertainment, to most important issues such as security and traffic management. Within this context, the AIDER system (AIDER is the acronym of Accident Information and Driver Emergency Rescue) is one of the most advanced multimedia mobile services targeted at emergency situations such as road accidents. The AIDER allows the interactive exchange of multimedia data (and in particular, audio, video and biomedical information) between the vehicle and a remote rescue centre, by using several different narrowband radio channels including cellular networks and satellite. In this paper an overview of the AIDER architecture is provided, focusing on the advanced video communication system.     

Online self-repair of FIR filters

Chip-level failure detection has been a target of research for some time, but today's very deep-submicron technology is forcing such research to move beyond detection. Repair, especially self-repair, has become very important for containing the susceptibility of today's chips. This article introduces a self-repair-solution for the digital FIR filter, one of the key blocks used in DSPs.     

Programmable built-in self-testing of embedded RAM clusters in system-on-chip architectures

Multiport memories are widely used as embedded cores in all communication system-on-chip devices. Due to their high complexity and very low accessibility, built-in self-test (BIST) is the most common solution implemented to test the different memories embedded in the system. This article presents a programmable BIST architecture based on a single microprogrammable BIST processor and a set of memory wrappers designed to simplify the test of a system containing a large number of distributed multiport memories of different sizes (number of bits, number of words), access protocols (asynchronous, synchronous), and timing.     

Effects of ageing on 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) neurotoxic effects on striatum and brainstem in the rat

In 3- and 18-month-old male Wistar rats, levels of dopamine (DA), dihydroxyphenylacetic acid (DOPAC), ascorbic acid (AA), dehydroascorbic acid (DHAA), noradrenaline (NA), uric acid, glutathione (GSH) and 1-methyl-4-phenylpyridinium ion (MPP+) were determined by HPLC in the striatum and/or in the brainstem 24 h after single injections of MPTP (12-35 mg/kg i.p.). Aged rats had lower baseline levels of AA and GSH, compared to young rats. In aged rats, MPTP 35 mg/kg induced a 70% death rate and a decrease in striatal DOPAC/DA ratio which was significantly correlated to MPP+ concentrations (r = -0.840, P < 0.005); in addition, MPTP did not increase AA oxidation. In the brainstem, the MPTP-induced decrease in NA levels and increase in uric acid levels were significantly correlated to the MPP+ concentrations (r = -0.709, P < 0.05, and r = +0.888, P < 0.001, respectively). In conclusion, evidence is given of a mechanism of toxicity of MPTP involving oxidative stress produced by xanthine oxidase; in addition, in aged rats the neuronal antioxidant system (levels of AA and GSH) is considerably lower than in young rats and may play an enabling role in the MPTP age-related neurotoxic effects on striatum and brainstem.     

Use of neural networks for quick and accurate auto-tuning of PID controller

With reference to a real industrial application of process control, some considerations are discussed concerning the accuracy of methods for auto-tuning of proportional, integral and derivative factor (PID). In particular, a theoretical–experimental approach is described, that allows to evaluate the adequateness of new methods for auto-tuning of PID, able to significantly reduce the time duration for auto-tuning with respect to traditional ones. This result has been achieved by using suitable techniques of experimental data processing, based on neural-networks algorithms, set for this specific application. The effect on described methodology of environmental and operating disturbances is also described.