PIGD are characterized by more severe disease manifestations at diagnosis and greater cognitive progression, more frequent hallucinations, psychosis as well as features of DDS than TD patients. We interpret these findings as expression of greater cortical and subcortical involvement in PIGD already at onset. Since PIGD/TD classification is very unstable at onset, our analysis based on stricter definition criteria provides important insight for clinical trial stratification and definition of related outcome measures.
PD_Manager is a mobile health platform designed to cover most of the aspects regarding the management of Parkinson's disease (PD) in a holistic approach. Patients are unobtrusively monitored using commercial wrist and insole sensors paired with a smartphone, to automatically estimate the severity of most of the PD motor symptoms. Besides motor symptoms monitoring, the patient's mobile application also provides various non-motor self-evaluation tests for assessing cognition, mood and nutrition to motivate them in becoming more active in managing their disease. All data from the mobile application and the sensors is transferred to a cloud infrastructure to allow easy access for clinicians and further processing. Clinicians can access this information using a separate mobile application that is specifically designed for their respective needs to provide faster and more accurate assessment of PD symptoms that facilitate patient evaluation. Machine learning techniques are used to estimate symptoms and disease progression trends to further enhance the provided information. The platform is also complemented with a decision support system (DSS) that notifies clinicians for the detection of new symptoms or the worsening of existing ones. As patient's symptoms are progressing, the DSS can also provide specific suggestions regarding appropriate medication changes.
Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the Arabidopsis thaliana model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of (component1, reaction, component2) triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at http://ropot.ijs.si/bio3graph/and can be utilised for modelling other biological systems, given that an adequate vocabulary is provided.
For any of the algorithms of an intelligent transportation system (ITS) to be effective, high-quality data are essential. In reality the data obtained in the field carry significant noise because of imperfections in the measurement devices. For example, the traffic volume data on different links of a network must be consistent and must satisfy the conservation of flow, but this condition is rarely met by the observed values. A way to adjust the observed values so that the adjusted values satisfy predetermined conditions, such as the flow conservation equations or any consistency requirements in a network, is proposed. The adjusted values are found to be as close to the observed value as possible by using the concept of fuzzy optimization. The method can be applied to any network configuration and can also estimate the traffic volumes for links for which traffic volume data may be missing. The method is so general that it can be applied to various transportation problems in which a set of observed or calculated values must be adjusted to satisfy some predetermined rigid relationships among the parameters.
As the models of transportation planning and engineering become more and more sophisticated, the quality of data that is used as input to the models is of critical importance to the integrity of the analysis. Several methods that adjust the field-traffic-volume data so that they become consistent and useful information for the subsequent analysis steps are examined. Consistency as satisfaction of flow conservation and other relationships underlying the network flow in question are defined. Six methods, including the manual method, are presented, and the logic and computational process are explained for each method. Except for the manual method, the methods are grouped into two general categories and discussed—one considers inconsistency in the data as a result of the statistical error and uses the classical-regression approach, and the other considers the observed value as the approximate value and uses the fuzzy-set theory. These methods are compared for their performance using an example problem. Transportation analysts’ alternative methods for volume adjustment are provided, and the analysts’ theoretical and practical implications are explained.
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