SIMSAFADIM-CLASTIC: A new approach to mathematical 3D forward simulation modelling for terrigenous and carbonate marine sedimentation

Most sedimentary modelling programs developed in recent years focus on either terrigenous or carbonate marine sedimentation. Nevertheless, only a few programs have attempted to consider mixed terrigenous-carbonate sedimentation, and most of these are two-dimensional, which is a major restriction since geological processes take place in 3D. This paper presents the basic concepts of a new 3D mathematical forward simulation model for clastic sediments, which was developed from SIMSAFADIM, a previous 3D carbonate sedimentation model. The new extended model, SIMSAFADIM-CLASTIC, simulates processes of autochthonous marine carbonate production and accumulation, together with clastic transport and sedimentation in three dimensions of both carbonate and terrigenous sediments. Other models and modelling strategies may also provide realistic and efficient tools for prediction of stratigraphic architecture and facies distribution of sedimentary deposits. However, SIMSAFADIM-CLASTIC becomes an innovative model that attempts to simulate different sediment types using a process-based approach, therefore being a useful tool for 3D prediction of stratigraphic architecture and facies distribution in sedimentary basins. This model is applied to the neogene Vallès-Penedès half-graben (western Mediterranean, NE Spain) to show the capacity of the program when applied to a realistic geologic situation involving interactions between terrigenous clastics and carbonate sediments.

A design science approach to support the assessment of disruptive technology : the Swiss mobile payment case

Abstract In this thesis we present the design of a systematic integrated computer-based approach for detecting potential disruptions from an industry perspective. Following the design science paradigm, we iteratively develop several multi-actor multi-criteria artifacts dedicated to environment scanning. The contributions of this thesis are both theoretical and practical. We demonstrate the successful use of multi-criteria decision-making methods for technology foresight. Furthermore, we illustrate the design of our artifacts using build and-evaluate loops supported with a field study of the Swiss mobile payment industry. To increase the relevance of this study, we systematically interview key Swiss experts for each design iteration. As a result, our research provides a realistic picture of the current situation in the Swiss mobile payment market and reveals previously undiscovered weak signals for future trends. Finally, we suggest a generic design process for environment scanning.

Community structure in mediterranean shallow lentic ecosystems: size-based vs. taxon-based approaches

The main environmental variables determining the community structure and the functioning of Mediterranean shallow lentic ecosystems are described. These ecosystems are characterized by the unpredictability of their water inputs and the high variability in their water level and physical and chemical composition. Variations in flooding, salinity, and water turnover are determinant in species composition and nutrient dynamics. Taxon-based and size-based approaches to the study of the community structure of aquatic organisms that colonise these ecosystems are also compared. The conventional taxonomic approach, based on the determination of species composition, has been used for the identification of patterns in species richness, distribution and temporal dynamics, and for ecological requirements of species and their potential use as ecological indicators. This taxonbased approach has been compared with a size-based approach, where individuals are classified by their size. Size-based approach gives complementary information about community structure and dynamics, especially when communities are dominated by a single species. The use of size diversity combined with species diversity is suggested for a more complete understanding of community structuring in this type of ecosystem. Detailed examples of two Mediterranean shallow lentic ecosystems, the salt marshes of the Empordà wetlands and the Espolla temporary karstic pond, which differ in hydrology and water origin, are used to discuss the suitability of these different approaches

Using niche-based models to improve the sampling of rare species

Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution models can be used to stratify the sampling and increase sampling efficiency. New data sampled are then used to improve the initial model. Applying this approach repeatedly is an adaptive process that may allow increasing the number of new occurrences found. We illustrate the approach with a case study of a rare and endangered plant species in Switzerland and a simulation experiment. Our field survey confirmed that the method helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high. In our simulations the model-based approach provided a significant improvement (by a factor of 1.8 to 4 times, depending on the measure) over simple random sampling. In terms of cost this approach may save up to 70% of the time spent in the field.

A novel approach to characterize clonality and differentiation of human melanoma-specific T cell responses: spontaneous priming and efficient boosting by vaccination.

Despite major progress in T lymphocyte analysis in melanoma patients, TCR repertoire selection and kinetics in response to tumor Ags remain largely unexplored. In this study, using a novel ex vivo molecular-based approach at the single-cell level, we identified a single, naturally primed T cell clone that dominated the human CD8(+) T cell response to the Melan-A/MART-1 Ag. The dominant clone expressed a high-avidity TCR to cognate tumor Ag, efficiently killed tumor cells, and prevailed in the differentiated effector-memory T lymphocyte compartment. TCR sequencing also revealed that this particular clone arose at least 1 year before vaccination, displayed long-term persistence, and efficient homing to metastases. Remarkably, during concomitant vaccination over 3.5 years, the frequency of the pre-existing clone progressively increased, reaching up to 2.5% of the circulating CD8 pool while its effector functions were enhanced. In parallel, the disease stabilized, but subsequently progressed with loss of Melan-A expression by melanoma cells. Collectively, combined ex vivo analysis of T cell differentiation and clonality revealed for the first time a strong expansion of a tumor Ag-specific human T cell clone, comparable to protective virus-specific T cells. The observed successful boosting by peptide vaccination support further development of immunotherapy by including strategies to overcome immune escape.

Resilient housing : a new resource-oriented approach

The institutional regimes framework has previously been applied to the institutional conditions that support or hinder the sustainability of housing stocks. This resource-based approach identifies the actors across different sectors that have an interest in housing, how they use housing, the mechanisms affecting their use (public policy, use rights, contracts, etc.) and the effects of their uses on the sustainability of housing within the context of the built environment. The potential of the institutional regimes framework is explored for its suitability to the many considerations of housing resilience. By identifying all the goods and services offered by the resource 'housing stock', researchers and decision-makers could improve the resilience of housing by better accounting for the ecosystem services used by housing, decreasing the vulnerability of housing to disturbances, and maximizing recovery and reorganization following a disturbance. The institutional regimes framework is found to be a promising tool for addressing housing resilience. Further questions are raised for translating this conceptual framework into a practical application underpinned with empirical data.

Toward Synchronous Extensible Dependency Grammar

Extensible Dependency Grammar (XDG; Debusmann, 2007) is a flexible, modular dependency grammarframework in which sentence analyses consist of multigraphs and processing takes the form of constraint satisfaction. This paper shows how XDGlends itself to grammar-driven machine translation and introduces the machinery necessary for synchronous XDG. Since the approach relies on a shared semantics, it resembles interlingua MT.It differs in that there are no separateanalysis and generation phases. Rather, translation consists of the simultaneousanalysis and generation of a single source-target sentence.

Taking on new challenges in multi-word unit processing for Machine Translation

This paper discusses the qualitativecomparative evaluation performed on theresults of two machine translation systemswith different approaches to the processing ofmulti-word units. It proposes a solution forovercoming the difficulties multi-word unitspresent to machine translation by adopting amethodology that combines the lexicongrammar approach with OpenLogos ontologyand semantico-syntactic rules. The paper alsodiscusses the importance of a qualitativeevaluation metrics to correctly evaluate theperformance of machine translation engineswith regards to multi-word units.

Patterns of neurovascular compression in patients with classic trigeminal neuralgia: A high-resolution MRI-based study.

PURPOSE: To describe the anatomical characteristics and patterns of neurovascular compression in patients suffering classic trigeminal neuralgia (CTN), using high-resolution magnetic resonance imaging (MRI). MATERIALS AND METHODS: The analysis of the anatomy of the trigeminal nerve, brain stem and the vascular structures related to this nerve was made in 100 consecutive patients treated with a Gamma Knife radiosurgery for CTN between December 1999 and September 2004. MRI studies (T1, T1 enhanced and T2-SPIR) with axial, coronal and sagital simultaneous visualization were dynamically assessed using the software GammaPlan?. Three-dimensional reconstructions were also developed in some representative cases. RESULTS: In 93 patients (93%), there were one or several vascular structures in contact, either, with the trigeminal nerve, or close to its origin in the pons. The superior cerebellar artery was involved in 71 cases (76%). Other vessels identified were the antero-inferior cerebellar artery, the basilar artery, the vertebral artery, and some venous structures. Vascular compression was found anywhere along the trigeminal nerve. The mean distance between the nerve compression and the origin of the nerve in the brainstem was 3.76±2.9mm (range 0-9.8mm). In 39 patients (42%), the vascular compression was located proximally and in 42 (45%) the compression was located distally. Nerve dislocation or distortion by the vessel was observed in 30 cases (32%). CONCLUSIONS: The findings of this study are similar to those reported in surgical and autopsy series. This non-invasive MRI-based approach could be useful for diagnostic and therapeutic decisions in CTN, and it could help to understand its pathogenesis.

Content value chains modelling using a copyright ontology

Existing digital rights management (DRM) systems, initiatives like Creative Commons or research works as some digital rights ontologies provide limited support for content value chains modelling and management. This is becoming a critical issue as content markets start to profit from the possibilities of digital networks and the World Wide Web. The objective is to support the whole copyrighted content value chain across enterprise or business niches boundaries. Our proposal provides a framework that accommodates copyright law and a rich creation model in order to cope with all the creation life cycle stages. The dynamic aspects of value chains are modelled using a hybrid approach that combines ontology-based and rule-based mechanisms. The ontology implementation is based on Web Ontology Language and Description Logic (OWL-DL) reasoners, are directly used for license checking. On the other hand, for more complex aspects of the dynamics of content value chains, rule languages are the choice.

Colligation and Cross Moment-Based Approaches for Independent Component Analysis

Diplomityössä on käsitelty uudenlaisia menetelmiä riippumattomien komponenttien analyysiin(ICA): Menetelmät perustuvat colligaatioon ja cross-momenttiin. Colligaatio menetelmä perustuu painojen colligaatioon. Menetelmässä on käytetty kahden tyyppisiä todennäköisyysjakaumia yhden sijasta joka perustuu yleiseen itsenäisyyden kriteeriin. Työssä on käytetty colligaatio lähestymistapaa kahdella asymptoottisella esityksellä. Gram-Charlie ja Edgeworth laajennuksia käytetty arvioimaan todennäköisyyksiä näissä menetelmissä. Työssä on myös käytetty cross-momentti menetelmää joka perustuu neljännen asteen cross-momenttiin. Menetelmä on hyvin samankaltainen FastICA algoritmin kanssa. Molempia menetelmiä on tarkasteltu lineaarisella kahden itsenäisen muuttajan sekoituksella. Lähtö signaalit ja sekoitetut matriisit ovattuntemattomia signaali lähteiden määrää lukuunottamatta. Työssä on vertailtu colligaatio menetelmään ja sen modifikaatioita FastICA:an ja JADE:en. Työssä on myös tehty vertailu analyysi suorituskyvyn ja keskusprosessori ajan suhteen cross-momenttiin perustuvien menetelmien, FastICA:n ja JADE:n useiden sekoitettujen parien kanssa.

Experience-based Auditory Predictions Modulate Brain Activity to Silence as Do Real Sounds.

Interactions between stimuli's acoustic features and experience-based internal models of the environment enable listeners to compensate for the disruptions in auditory streams that are regularly encountered in noisy environments. However, whether auditory gaps are filled in predictively or restored a posteriori remains unclear. The current lack of positive statistical evidence that internal models can actually shape brain activity as would real sounds precludes accepting predictive accounts of filling-in phenomenon. We investigated the neurophysiological effects of internal models by testing whether single-trial electrophysiological responses to omitted sounds in a rule-based sequence of tones with varying pitch could be decoded from the responses to real sounds and by analyzing the ERPs to the omissions with data-driven electrical neuroimaging methods. The decoding of the brain responses to different expected, but omitted, tones in both passive and active listening conditions was above chance based on the responses to the real sound in active listening conditions. Topographic ERP analyses and electrical source estimations revealed that, in the absence of any stimulation, experience-based internal models elicit an electrophysiological activity different from noise and that the temporal dynamics of this activity depend on attention. We further found that the expected change in pitch direction of omitted tones modulated the activity of left posterior temporal areas 140-200 msec after the onset of omissions. Collectively, our results indicate that, even in the absence of any stimulation, internal models modulate brain activity as do real sounds, indicating that auditory filling in can be accounted for by predictive activity.

Structure-Based, Rational Design of T Cell Receptors.

Adoptive cell transfer using engineered T cells is emerging as a promising treatment for metastatic melanoma. Such an approach allows one to introduce T cell receptor (TCR) modifications that, while maintaining the specificity for the targeted antigen, can enhance the binding and kinetic parameters for the interaction with peptides (p) bound to major histocompatibility complexes (MHC). Using the well-characterized 2C TCR/SIYR/H-2K(b) structure as a model system, we demonstrated that a binding free energy decomposition based on the MM-GBSA approach provides a detailed and reliable description of the TCR/pMHC interactions at the structural and thermodynamic levels. Starting from this result, we developed a new structure-based approach, to rationally design new TCR sequences, and applied it to the BC1 TCR targeting the HLA-A2 restricted NY-ESO-1157-165 cancer-testis epitope. Fifty-four percent of the designed sequence replacements exhibited improved pMHC binding as compared to the native TCR, with up to 150-fold increase in affinity, while preserving specificity. Genetically engineered CD8(+) T cells expressing these modified TCRs showed an improved functional activity compared to those expressing BC1 TCR. We measured maximum levels of activities for TCRs within the upper limit of natural affinity, K D = ∼1 - 5 μM. Beyond the affinity threshold at K D < 1 μM we observed an attenuation in cellular function, in line with the "half-life" model of T cell activation. Our computer-aided protein-engineering approach requires the 3D-structure of the TCR-pMHC complex of interest, which can be obtained from X-ray crystallography. We have also developed a homology modeling-based approach, TCRep 3D, to obtain accurate structural models of any TCR-pMHC complexes when experimental data is not available. Since the accuracy of the models depends on the prediction of the TCR orientation over pMHC, we have complemented the approach with a simplified rigid method to predict this orientation and successfully assessed it using all non-redundant TCR-pMHC crystal structures available. These methods potentially extend the use of our TCR engineering method to entire TCR repertoires for which no X-ray structure is available. We have also performed a steered molecular dynamics study of the unbinding of the TCR-pMHC complex to get a better understanding of how TCRs interact with pMHCs. This entire rational TCR design pipeline is now being used to produce rationally optimized TCRs for adoptive cell therapies of stage IV melanoma.

Brain dynamics sustaining rapid rule extraction from speech

Language acquisition is a complex process that requires the synergic involvement of different cognitive functions, which include extracting and storing the words of the language and their embedded rules for progressive acquisition of grammatical information. As has been shown in other fields that study learning processes, synchronization mechanisms between neuronal assemblies might have a key role during language learning. In particular, studying these dynamics may help uncover whether different oscillatory patterns sustain more item-based learning of words and rule-based learning from speech input. Therefore, we tracked the modulation of oscillatory neural activity during the initial exposure to an artificial language, which contained embedded rules. We analyzed both spectral power variations, as a measure of local neuronal ensemble synchronization, as well as phase coherence patterns, as an index of the long-range coordination of these local groups of neurons. Synchronized activity in the gamma band (2040 Hz), previously reported to be related to the engagement of selective attention, showed a clear dissociation of local power and phase coherence between distant regions. In this frequency range, local synchrony characterized the subjects who were focused on word identification and was accompanied by increased coherence in the theta band (48 Hz). Only those subjects who were able to learn the embedded rules showed increased gamma band phase coherence between frontal, temporal, and parietal regions.

Segmental Durations of Speech

This dissertation considers the segmental durations of speech from the viewpoint of speech technology, especially speech synthesis. The idea is that better models of segmental durations lead to higher naturalness and better intelligibility. These features are the key factors for better usability and generality of synthesized speech technology. Even though the studies are based on a Finnish corpus the approaches apply to all other languages as well. This is possibly due to the fact that most of the studies included in this dissertation are about universal effects taking place on utterance boundaries. Also the methods invented and used here are suitable for any other study of another language. This study is based on two corpora of news reading speech and sentences read aloud. The other corpus is read aloud by a 39-year-old male, whilst the other consists of several speakers in various situations. The use of two corpora is twofold: it involves a comparison of the corpora and a broader view on the matters of interest. The dissertation begins with an overview to the phonemes and the quantity system in the Finnish language. Especially, we are covering the intrinsic durations of phonemes and phoneme categories, as well as the difference of duration between short and long phonemes. The phoneme categories are presented to facilitate the problem of variability of speech segments. In this dissertation we cover the boundary-adjacent effects on segmental durations. In initial positions of utterances we find that there seems to be initial shortening in Finnish, but the result depends on the level of detail and on the individual phoneme. On the phoneme level we find that the shortening or lengthening only affects the very first ones at the beginning of an utterance. However, on average, the effect seems to shorten the whole first word on the word level. We establish the effect of final lengthening in Finnish. The effect in Finnish has been an open question for a long time, whilst Finnish has been the last missing piece for it to be a universal phenomenon. Final lengthening is studied from various angles and it is also shown that it is not a mere effect of prominence or an effect of speech corpus with high inter- and intra-speaker variation. The effect of final lengthening seems to extend from the final to the penultimate word. On a phoneme level it reaches a much wider area than the initial effect. We also present a normalization method suitable for corpus studies on segmental durations. The method uses an utterance-level normalization approach to capture the pattern of segmental durations within each utterance. This prevents the impact of various problematic variations within the corpora. The normalization is used in a study on final lengthening to show that the results on the effect are not caused by variation in the material. The dissertation shows an implementation and prowess of speech synthesis on a mobile platform. We find that the rule-based method of speech synthesis is a real-time software solution, but the signal generation process slows down the system beyond real time. Future aspects of speech synthesis on limited platforms are discussed. The dissertation considers ethical issues on the development of speech technology. The main focus is on the development of speech synthesis with high naturalness, but the problems and solutions are applicable to any other speech technology approaches.