Imaging and Characterisation of Dirt Particles in Pulp and Paper

Dirt counting and dirt particle characterisation of pulp samples is an important part of quality control in pulp and paper production. The need for an automatic image analysis system to consider dirt particle characterisation in various pulp samples is also very critical. However, existent image analysis systems utilise a single threshold to segment the dirt particles in different pulp samples. This limits their precision. Based on evidence, designing an automatic image analysis system that could overcome this deficiency is very useful. In this study, the developed Niblack thresholding method is proposed. The method defines the threshold based on the number of segmented particles. In addition, the Kittler thresholding is utilised. Both of these thresholding methods can determine the dirt count of the different pulp samples accurately as compared to visual inspection and the Digital Optical Measuring and Analysis System (DOMAS). In addition, the minimum resolution needed for acquiring a scanner image is defined. By considering the variation in dirt particle features, the curl shows acceptable difference to discriminate the bark and the fibre bundles in different pulp samples. Three classifiers, called k-Nearest Neighbour, Linear Discriminant Analysis and Multi-layer Perceptron are utilised to categorize the dirt particles. Linear Discriminant Analysis and Multi-layer Perceptron are the most accurate in classifying the segmented dirt particles by the Kittler thresholding with morphological processing. The result shows that the dirt particles are successfully categorized for bark and for fibre bundles.

Cognitive Functions After Traumatic Brain Injury. A 30-year Follow-up Study

Many cognitive deficits after TBI (traumatic brain injury) are well known, such as memory and concentration problems, as well as reduced information-processing speed. What happens to patients and cognitive functioning after immediate recovery is poorly known. Cognitive functioning is flexible and may be influenced by genetic, psychological and environmental factors decades after TBI. The general aim of this thesis was to describe the long-term cognitive course after TBI, to find variables that may contribute to it, and how the cognitive functions after TBI are associated with specific medical factors and reduced survival. The original study group consisted of 192 patients with TBI who were originally assessed with the Mild Deterioration Battery (MDB) on average two years after the injury, during the years 1966 – 1972. During a 30-year follow-up, we studied the risks for reduced survival, and the mortality of the patients was compared with the general population using the Standardized Mortality Ratio (SMR). Sixty-one patients were re-assessed during 1998-2000. These patients were evaluated with the MDB, computerized testing, and with various other neuropsychological methods for attention and executive functions. Apolipoprotein-E (ApoE) genotyping and magnetic resonance imaging (MRI) based on volumetric analysis of the hippocampus and lateral ventricles were performed. Depressive symptoms were evaluated with the short form of the Beck depression inventory. The cognitive performance at follow-up was compared with a control group that was similar to the study group in regard to age and education. The cognitive outcome of the patients with TBI varied after three decades. The majority of the patients showed a decline in their cognitive level, the rest either improved or stayed at the same level. Male gender and higher age at injury were significant risk factors for the decline. Whereas most cognitive domains declined during the follow-up, semantic memory behaved in the opposite way, showing recovery after TBI. In the follow-up assessment, the memory decline and impairments in the set-shifting domain of executive functions were associated with MRI-volumetric measures, whereas reduction in information-processing speed was not associated with the MRI measures. The presence of local contusions was only weakly associated with cognitive functions. Only few cognitive methods for attention were capable of discriminating TBI patients with and without depressive symptoms. On the other hand, most complex attentional tests were sensitive enough to discriminate TBI patients (non-depressive) from controls. This means that complex attention functions, mediated by the frontal lobes, are relatively independent of depressive symptoms post-TBI. The presence of ApoE4 was associated with different kinds of memory processes including verbal and visual episodic memory, semantic memory and verbal working memory, depending on the length of time since TBI. Many other cognitive processes were not affected by the presence of ApoE4. Age at injury and poor vocational outcome were independent risk factors for reduced survival in the multivariate analysis. Late mortality was higher among younger subjects (age < 40 years at death) compared with the general population which should be borne in mind when assessing the need for rehabilitation services and long-term follow-up after TBI.

Electroactive ion exchange membranes based on conducting polymers

Ion exchange membranes are indispensable for the separation of ionic species. They can discriminate between anions and cations depending on the type of fixed ionic group present in the membrane. These conventional ion exchange membranes (CIX) have exceptional ionic conductivity, which is advantageous in various electromembrane separation processes such as electrodialysis, electrodeionisation and electrochemical ion exchange. The main disadvantage of CIX membranes is their high electrical resistance owing to the fact that the membranes are electronically non conductive. An alternative can be electroactive ion exchange membranes, which are ionically and electronically conducting. Polypyrrole (PPy) is a type of electroactive ion exchange material as well as a commonly known conducting polymer. When PPy membranes are repeatedly reduced and oxidised, ions are pumped through the membrane. The main aim of this thesis was to develop electroactive cation transport membranes based on PPy for the selective transport of divalent cations. Membranes developed composed of PPy films deposited on commercially available support materials. To carry out this study, cation exchange membranes based on PPy doped with immobile anions were prepared. Two types of dopant anions known to interact with divalent metal ions were considered, namely 4-sulphonic calix[6]arene (C6S) and carboxylated multiwalled carbon nanotubes (CNT). The transport of ions across membranes containing PPy doped with polystyrene sulphonate (PSS) and PPy doped with para-toluene sulphonate (pTS) was also studied in order to understand the nature of ion transport and permeability across PPy(CNT) and PPy(C6S) membranes. In the course of these studies, membrane characterisation was performed using electrochemical quartz crystal microbalance (EQCM) and scanning electron microscopy (SEM). Permeability of the membranes towards divalent cations was explored using a two compartment transport cell. EQCM results demonstrated that the ion exchange behaviour of polypyrrole is dependent on a number of factors including the type of dopant anion present, the type of ions present in the surrounding medium, the scan rate used during the experiment and the previous history of the polymer film. The morphology of PPy films was found to change when the dopant anion was varied and even when the thickness of the film was altered in some cases. In nearly all cases the permeability of the membranes towards metal ions followed the order K+ > Ca2+ > Mn2+. The one exception was PPy(C6S), for which the permeability followed the order Ca2+ ≥ K+ > Mn2+ > Co2+ > Cr3+. The above permeability sequences show a strong dependence on the size of the metal ions with metal ions having the smallest hydrated radii exhibiting the highest flux. Another factor that affected the permeability towards metal ions was the thickness of the PPy films. Films with the least thickness showed higher metal ion fluxes. Electrochemical control over ion transport across PPy(CNT) membrane was obtained when films composed of the latter were deposited on track-etched Nucleopore® membranes as support material. In contrast, the flux of ions across the same film was concentration gradient dependent when the polymer was deposited on polyvinylidene difluoride membranes as support material. However, electrochemical control over metal ion transport was achieved with a bilayer type of PPy film consisting of PPy(pTS)/PPy(CNT), irrespective of the type of support material. In the course of studying macroscopic charge balance during transport experiments performed using a two compartment transport cell, it was observed that PPy films were non-permselective. A clear correlation between the change in pH in the receiving solution and the ions transported across the membrane was observed. A decrease in solution pH was detected when the polymer membrane acted primarily as an anion exchanger, while an increase in pH occurred when it functioned as a cation exchanger. When there was an approximately equal flux of anions and cations across the polymer membrane, the pH in the receiving solution was in the range 6 - 8. These observations suggest that macroscopic charge balance during the transport of cations and anions across polypyrrole membranes was maintained by introduction of anions (OH-) and cations (H+) produced via electrolysis of water.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

Recognition of nucleic acids by metal ion complexes

Metal-ion-mediated base-pairing of nucleic acids has attracted considerable attention during the past decade, since it offers means to expand the genetic code by artificial base-pairs, to create predesigned molecular architecture by metal-ion-mediated inter- or intra-strand cross-links, or to convert double stranded DNA to a nano-scale wire. Such applications largely depend on the presence of a modified nucleobase in both strands engaged in the duplex formation. Hybridization of metal-ion-binding oligonucleotide analogs with natural nucleic acid sequences has received much less attention in spite of obvious applications. While the natural oligonucleotides hybridize with high selectivity, their affinity for complementary sequences is inadequate for a number of applications. In the case of DNA, for example, more than 10 consecutive Watson-Crick base pairs are required for a stable duplex at room temperature, making targeting of sequences shorter than this challenging. For example, many types of cancer exhibit distinctive profiles of oncogenic miRNA, the diagnostics of which is, however, difficult owing to the presence of only short single stranded loop structures. Metallo-oligonucleotides, with their superior affinity towards their natural complements, would offer a way to overcome the low stability of short duplexes. In this study a number of metal-ion-binding surrogate nucleosides were prepared and their interaction with nucleoside 5´-monophosphates (NMPs) has been investigated by 1H NMR spectroscopy. To find metal ion complexes that could discriminate between natural nucleobases upon double helix formation, glycol nucleic acid (GNA) sequences carrying a PdII ion with vacant coordination sites at a predetermined position were synthesized and their affinity to complementary as well as mismatched counterparts quantified by UV-melting measurements.