Age estimation in common sole Solea solea larvae: validation of daily increments and evaluation of a pattern recognition technique

Close similarities have been found between the otoliths of sea-caught and laboratory-reared larvae of the common sole Solea solea (L.), given appropriate temperatures and nourishment of the latter. But from hatching to mouth formation. and during metamorphosis, sole otoliths have proven difficult to read because the increments may be less regular and low contrast. In this study, the growth increments in otoliths of larvae reared at 12 degrees C were counted by light microscopy to test the hypothesis of daily deposition, with some results verified using scanning electron microscopy (SEM), and by image analysis in order to compare the reliability of the 2 methods in age estimation. Age was first estimated (in days posthatch) from light micrographs of whole mounted otoliths. Counts were initiated from the increment formed at the time of month opening (Day 4). The average incremental deposition rate was consistent with the daily hypothesis. However, the light-micrograph readings tended to underestimate the mean ages of the larvae. Errors were probably associated with the low-contrast increments: those deposited after the mouth formation during the transition to first feeding, and those deposited from the onset of eye migration (about 20 d posthatch) during metamorphosis. SEM failed to resolve these low-contrast areas accurately because of poor etching. A method using image analysis was applied to a subsample of micrograph-counted otoliths. The image analysis was supported by an algorithm of pattern recognition (Growth Demodulation Algorithm, GDA). On each otolith, the GDA method integrated the growth pattern of these larval otoliths to averaged data from different radial profiles, in order to demodulate the exponential trend of the signal before spectral analysis (Fast Fourier Transformation, FFT). This second method both allowed more precise designation of increments, particularly for low-contrast areas, and more accurate readings but increased error in mean age estimation. The variability is probably due to a still rough perception of otolith increments by the GDA method, counting being achieved through a theoretical exponential pattern and mean estimates being given by FFT. Although this error variability was greater than expected, the method provides for improvement in both speed and accuracy in otolith readings.

Innate immune humoral factors, C1q and factor H, with differential pattern recognition properties, alter macrophage response to carbon nanotubes

Interaction between the complement system and carbon nanotubes (CNTs) can modify their intended biomedical applications. Pristine and derivatised CNTs can activate complement primarily via the classical pathway which enhances uptake of CNTs and suppresses pro-inflammatory response by immune cells. Here, we report that the interaction of C1q, the classical pathway recognition molecule, with CNTs involves charge pattern and classical pathway activation that is partly inhibited by factor H, a complement regulator. C1q and its globular modules, but not factor H, enhanced uptake of CNTs by macrophages and modulated the pro-inflammatory immune response. Thus, soluble complement factors can interact differentially with CNTs and alter the immune response even without complement activation. Coating CNTs with recombinant C1q globular heads offers a novel way of controlling classical pathway activation in nanotherapeutics. Surprisingly, the globular heads also enhance clearance by phagocytes and down-regulate inflammation, suggesting unexpected complexity in receptor interaction. From the Clinical Editor: Carbon nanotubes (CNTs) maybe useful in the clinical setting as targeting drug carriers. However, it is also well known that they can interact and activate the complement system, which may have a negative impact on the applicability of CNTs. In this study, the authors functionalized multi-walled CNT (MWNT), and investigated the interaction with the complement pathway. These studies are important so as to gain further understanding of the underlying mechanism in preparation for future use of CNTs in the clinical setting.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Prion crystalization model and its application to recognition pattern

This paper introduces APA (?Artificial Prion Assembly?): a pattern recognition system based on artificial prion crystalization. Specifically, the system exhibits the capability to classify patterns according to the resulting prion self- assembly simulated with cellular automata. Our approach is inspired in the biological process of proteins aggregation, known as prions, which are assembled as amyloid fibers related with neurodegenerative disorders.

Il vulcanismo esplosivo : l'isola Ferdinandea: eruzione del 1831 nel mar di Sicilia

Il contenuto di questo volume non vuole rappresentare un testo didattico per lo studio in generale della vulcanologia in quanto in esso si tratta unicamente quell’a-spetto della disciplina che riguarda il vulcanismo esplosivo. In tal senso l’autore ritiene che questo testo possa essere utile per gli studenti di Scienze Geologiche che, vivendo nelle aree vulcaniche italiane di età quaternaria ed anche attive, possano, da laureati, svolgere attività professionali mirate alla individuazione e definizione di Pericolosità, Vulnerabilità e Rischio Vulcanico. Trattare gli argomenti che seguono non è stato facile e forse si poteva, in alcuni casi, renderli più semplici, ma talvolta la semplicità non sempre è sinonimo di precisione; inoltre, per descrivere certi aspetti non quantitativi si è costretti ad utilizzare un linguaggio quanto più possibile “ad hoc”. L’autore ha svolto la propria attività di ricerca in aree vulcaniche, sia in Italia che all’estero. Le ricerche in Italia sono state da sempre concentrate nelle aree di vulcanismo attivo in cui l’attività del vulcanologo è finalizzata fondamentalmente alla definizione della Pericolosità Vulcanica supporto indispensabile per la definizione dell’aree a Rischio Vulcanico, intendendo per Rischio il prodotto della Pericolosità per il Danno in termini, questo, di numero di vite umane ovvero di valore monetario dei beni a rischio nell’area vulcanica attiva. Le ricerche svolte dall’autore in Africa Orientale (Etiopia e Somalia) e nello Yemen hanno contribuito ad assimilare i concetti di vulcanologia regionale, rappresentata dall’ampia diffusione del vulcanismo di plateau, variabile per spessore dai 1500 ai 3000 metri, fra i quali si inseriscono, nella depressione dell’Afar, catene vulcaniche inquadrabili, dal punto di vista geodinamico, come “oceaniche” alcune delle quali attive e che si sviluppano per decine/centinaia di chilometri. Nelle aree vulcaniche italiane le difficoltà che sorgono durante il rilevamento risiedono nella scarsa continuità di affioramenti, talvolta incompleti per la descrizione delle variazioni di facies piroclastiche, non disgiunta dalla fitta vegetazione ovvero ur banizzazione specialmente nelle aree di vulcanismo attivo. Il rilevamento vulcanologico richiede competenze e l’adozione di scale adatte a poter cartografare le variazioni di facies piroclastiche che, a differenza dalle assise sedimentarie, in un’area vulcanica possono essere diffuse arealmente soltanto per alcune centinaia di metri. I metodi di studio delle rocce piroclastiche sono del tutto simili a quelli che si usano per le rocce clastiche, cioè dall’analisi delle strutture e delle tessiture alla litologica fino a quella meccanica; su questi clasti inoltre le determinazioni della densità, della mineralogia e della geochimica (Elementi in tracce e Terre Rare), ottenute sulla frazione vetrosa, rappresentano parametri talvolta identificativi di un’area vulcanica sorgente. Non esistono testi nei quali venga descritto come si debba operare nelle aree vulcaniche per le quali l’unica certezza unificante è rappresentata dall’evidenza che, nelle sequenze stratigrafiche, il termine al top rappresenta quello più relativamente recente mentre quello alla base indica il termine relativo più vecchio. Quanto viene riportato in questo testo nasce dall’esperienza che è stata acquisita nel tempo attraverso una costante azione di rilevamento che rappresenta l’uni- ca sorgente di informazione che un vulcanologo deve ricavare attraverso un attento esame dei depositi vulcanici (dalla litologia alla mineralogia, alla tessitura, etc.) la cui distribuzione, talvolta, può assumere un carattere interegionale in Italia nell’ambito dell’Olocene. Soltanto l’esperienza acquisita con il rilevamento produce, in un’area di vulcanismo attivo, risultati positivi per la definizione della Pericolosità, sapendo però che le aree vulcaniche italiane presentano caratteristiche ampiamente differenti e di conseguenza il modo di operare non può essere sempre lo stesso. Un esempio? Immaginate di eseguire un rilevamento vulcanico prima al Somma-Vesuvio e poi nei Campi Flegrei: sono mondi completamente differenti. L’autore desidera ribadire che questo testo si basa sulla esperienza acquisita sia come geologo sia come docente di Vulcanologia; pertanto il libro potrà forse risultare più o meno bilanciato, in forza dell’argomento trattato, in quanto durante l’attività di ricerca l’autore, come tutti, ha affrontato alcuni argomenti più di altri. Questo approccio può essere considerato valido per chiunque voglia scrivere un libro in maniera autonoma e originale, non limitandosi, come molte volte avviene, a tradurre in italiano un libro su tematiche analoghe diffuso, ad esempio, nel mondo anglosassone.Diversamente, si sarebbe potuto concepire un libro come un collage di capitoli scritti da vari autori, che magari avevano esperienza più specifica nei singoli argomenti, ma in tal senso si sarebbe snaturato lo spirito con cui si è impostato il progetto. L’autore, infine, ha fatto ricorso al contributo di altri autorevoli colleghi solo per temi importantissimi, ma in qualche modo complementari rispetto al corpus costitutivo del Vulcanismo Esplosivo.

Rilevamento geologico della zona del Passo Rolle (TN) con elementi di geomeccanica

Nel lavoro vengono presentati i risultati del rilevamento geologico svolto nell'area di San Martino di Castrozza, nel mese di giugno 2022, durante il campo geologico. L'approfondimento tematico verte sull'analisi di stabilità di versante nel Monte Castellazzo. Gli studi sono stati accompagnati dal rilevamento geomeccanico che ha permesso di determinare i parametri necessari alla caratterizzazione dell'ammasso e alle verifiche cinematiche, e mediante un softwere di plottare i dati in degli stereoneit per definire gli eventi di instabilità associati ad ogni settore del Monte Castellazzo.

Recognition of noisy images by PLL networks

We use networks composed of three phase-locked loops (PLLs), where one of them is the master, for recognizing noisy images. The values of the coupling weights among the PLLs control the noise level which does not affect the successful identification of the input image. Analytical results and numerical tests are presented concerning the scheme performance. (c) 2008 Elsevier B.V. All rights reserved.

Human cortical processing of colour and pattern

The present study investigates human visual processing of simple two-colour patterns using a delayed match to sample paradigm with positron emission tomography (PET). This study is unique in that we specifically designed the visual stimuli to be the same for both pattern and colour recognition with all patterns being abstract shapes not easily verbally coded composed of two-colour combinations. We did this to explore those brain regions required for both colour and pattern processing and to separate those areas of activation required for one or the other. We found that both tasks activated similar occipital regions, the major difference being more extensive activation in pattern recognition. A right-sided network that involved the inferior parietal lobule, the head of the caudate nucleus, and the pulvinar nucleus of the thalamus was common to both paradigms. Pattern recognition also activated the left temporal pole and right lateral orbital gyrus, whereas colour recognition activated the left fusiform gyrus and several right frontal regions. (C) 2001 Wiley-Liss, Inc.

A new approach to real time traffic sign recognition based on colour information

The automatic interpretation of conventional traffic signs is very complex and time consuming. The paper concerns an automatic warning system for driving assistance. It does not interpret the standard traffic signs on the roadside; the proposal is to incorporate into the existing signs another type of traffic sign whose information will be more easily interpreted by a processor. The type of information to be added is profuse and therefore the most important object is the robustness of the system. The basic proposal of this new philosophy is that the co-pilot system for automatic warning and driving assistance can interpret with greater ease the information contained in the new sign, whilst the human driver only has to interpret the "classic" sign. One of the codings that has been tested with good results and which seems to us easy to implement is that which has a rectangular shape and 4 vertical bars of different colours. The size of these signs is equivalent to the size of the conventional signs (approximately 0.4 m2). The colour information from the sign can be easily interpreted by the proposed processor and the interpretation is much easier and quicker than the information shown by the pictographs of the classic signs

Assessment of Severe Apnoea through Voice Analysis, Automatic Speech, and Speaker Recognition Techniques

This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.

Quantitative proteomics reveals subset-specific viral recognition in dendritic cells.

Dendritic cell (DC) populations consist of multiple subsets that are essential orchestrators of the immune system. Technological limitations have so far prevented systems-wide accurate proteome comparison of rare cell populations in vivo. Here, we used high-resolution mass spectrometry-based proteomics, combined with label-free quantitation algorithms, to determine the proteome of mouse splenic conventional and plasmacytoid DC subsets to a depth of 5,780 and 6,664 proteins, respectively. We found mutually exclusive expression of pattern recognition pathways not previously known to be different among conventional DC subsets. Our experiments assigned key viral recognition functions to be exclusively expressed in CD4(+) and double-negative DCs. The CD8alpha(+) DCs largely lack the receptors required to sense certain viruses in the cytoplasm. By avoiding activation via cytoplasmic receptors, including retinoic acid-inducible gene I, CD8alpha(+) DCs likely gain a window of opportunity to process and present viral antigens before activation-induced shutdown of antigen presentation pathways occurs.

Automatic recognition of postural allocations.

A significant part of daily energy expenditure may be attributed to non-exercise activity thermogenesis and exercise activity thermogenesis. Automatic recognition of postural allocations such as standing or sitting can be used in behavioral modification programs aimed at minimizing static postures. In this paper we propose a shoe-based device and related pattern recognition methodology for recognition of postural allocations. Inexpensive technology allows implementation of this methodology as a part of footwear. The experimental results suggest high efficiency and reliability of the proposed approach.

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm