Loan quality, ownership and efficiency of Indian banks : A bootstrap truncated regression approach

Registration-by-regression of coronary CTA and X-ray angiography

We evaluate the integration of 3D preoperative computed tomography angiography of the coronary arteries with intraoperative 2D X-ray angiographies by a recently proposed novel registration-by-regression method. The method relates image features of 2D projection images to the transformation parameters of the 3D image. We compared different sets of features and studied the influence of preprocessing the training set. For the registration evaluation, a gold standard was developed from eight X-ray angiography sequences from six different patients. The alignment quality was measured using the 3D mean target registration error (mTRE). The registration-by-regression method achieved moderate accuracy (median mTRE of 15 mm) on real images. It does therefore not provide yet a complete solution to the 3D–2D registration problem but it could be used as an initialisation method to eliminate the need for manual initialisation.

Flexible regression models for functional neuroimaging

Current practice for analysing functional neuroimaging data is to average the brain signals recorded at multiple sensors or channels on the scalp over time across hundreds of trials or replicates to eliminate noise and enhance the underlying signal of interest. These studies recording brain signals non-invasively using functional neuroimaging techniques such as electroencephalography (EEG) and magnetoencephalography (MEG) generate complex, high dimensional and noisy data for many subjects at a number of replicates. Single replicate (or single trial) analysis of neuroimaging data have gained focus as they are advantageous to study the features of the signals at each replicate without averaging out important features in the data that the current methods employ. The research here is conducted to systematically develop flexible regression mixed models for single trial analysis of specific brain activities using examples from EEG and MEG to illustrate the models. This thesis follows three specific themes: i) artefact correction to estimate the `brain' signal which is of interest, ii) characterisation of the signals to reduce their dimensions, and iii) model fitting for single trials after accounting for variations between subjects and within subjects (between replicates). The models are developed to establish evidence of two specific neurological phenomena - entrainment of brain signals to an $\alpha$ band of frequencies (8-12Hz) and dipolar brain activation in the same $\alpha$ frequency band in an EEG experiment and a MEG study, respectively.

Generation of a business plan for a logistics service provider

The purpose of this Master’s Thesis was to study the suitability of transportation of liquid wastes to the portfolio of the case company. After the preliminary study the waste types were narrowed down to waste oil and oily waste from ports. The thesis was executed by generating a business plan. The qualitative research of this Master’s Thesis was executed as a case study by collecting information from multiple sources. The business plan was carried out by first familiarizing oneself with literature related to business planning which was then used as a base for the interview of the customer and interviews of the personnel of the case company. Additionally, internet sources and informal conversational interviews with the personnel of the case company were used and these interviews took place during the preliminary study and this thesis. The results of this thesis describe the requirements for the case company that must be met to be able to start operations. Import of waste oil fits perfectly to the portfolio of the case company and it doesn’t require any big investments. Success of the import of waste oil is affected by price of crude oil, exchange rate of ruble and legislation among others. Transportation of oily waste from ports, in turn, is not a core competence of the case company so more actions are required to start operating such as subcontracting with a waste management company.

Development of Imatra`s logistics hub as a part of Nordic region

This thesis is dedicated to enhancement and development of Imatra`s logistics potential in order to increase its key parameters and improve the efficiency of the region. To find out the most promising logistics projects was proposed a tool “integral-matrix analysis” which enables to make the priority among the list of proposed projects. Description and functionality of the tool are explained in detail. As a result of analysis, the list of priority projects for the development of the region is presented. Project with the greatest potential is implemented in the thesis work. In conclusion, recommendations for the further development of economic potential of the region are given. The thesis is basically focused on literature review, overlook of secondary and primary data (including the results of the interviews, which were carried out among companies that represent the logistics market). Primary data was collected in interviews with the representatives of the companies, who regularly use logistics services. Total effects that make various Russian regions and companies on the Finnish logistics is summed up and discussed.

Inbound logistics, the last mile and intermodal high capacity transport – the case of Jula in Sweden

Some of the biggest challenges for intermodal transport competitiveness are the extra handling costs and pre- and post-haulage costs. This paper investigates the use of Intermodal High Capacity Transport (IHCT) for the intermodal transport chain in general and to pre-and post-haulage in particular. The aim is not only to measure the cost reductions from using larger vehicles but to understand how better management of inbound flows through increased integration of logistics processes can increase the efficiency of the last mile. The paper analyses the haulage of two 40 foot containers simultaneously when part of an intermodal transport chain. Data were collected from a demonstration project in Sweden, where permission was obtained to use longer vehicles on an approved route to and from the nearest intermodal terminal. Results indicate substantial cost savings from using longer vehicles for pre- and post-haulage. In addition, the business model whereby the shipper purchased their own chassis and permission was obtained to access the terminal after hours for collecting pre-loaded chassis brought additional cost and planning benefits. The total cost saving was significant and potentially eliminates the cost deficit associated with the last mile.

Inbound logistics, the last mile and intermodal high capacity transport.

Some of the biggest challenges for intermodal transport competitiveness are the extra handling costs and pre- and post-haulage costs. This paper investigates the use of Intermodal High Capacity Transport (IHCT) for the intermodal transport chain in general and to pre-and post-haulage in particular. The aim is not only to measure the cost reductions from using larger vehicles but to understand how better management of inbound flows through increased integration of logistics processes can increase the efficiency of the last mile. The paper analyses the haulage of two 40 foot containers simultaneously when part of an intermodal transport chain. Data were collected from a demonstration project in Sweden, where permission was obtained to use longer vehicles on an approved route to and from the nearest intermodal terminal. Results indicate substantial cost savings from using longer vehicles for pre- and post-haulage. In addition, the business model whereby the shipper purchased their own chassis and permission was obtained to access the terminal after hours for collecting pre-loaded chassis brought additional cost and planning benefits. The total cost saving was significant and potentially eliminates the cost deficit associated with the last mile.

The spatial dimension of cycle logistics

US Cycle logistics is emerging as a promising alternative in urban freight transport. Compared to fossil fuelled vans, the use of cycles for delivering goods within urban areas offers advantages in terms of environmental friendliness, economic efficiency, flexibility, and liveability of urban neighbourhood. At the same time, cycle logistics has to face limits in terms of weight and volume of goods that can be delivered, distances that can be covered, and spatial urban structures that can be served. This latter issue has till now received less attention in the scientific literature: it is generally recognized that cycle logistics performs at its best in inner urban areas, but no systematic study has been realized to identify specific spatial requisites for the effectiveness of cycle logistics. This paper provides a brief review of the main issues that emerge from the literature over cycle logistics, and contributes to stimulate the debate over the spatial dimension of cycle logistics: it presents a classification of cycle logistics schemes, on the basis of their integration with other urban logistic facilities and of the spatial structure of delivery operations. A three-level classification is proposed, depending on the type of goods consolidation: only distribution without consolidation, consolidation in a fixed urban consolidation centre, or consolidation in a mobile depot; for each level, operational examples and case studies are provided. This systematizing typology could support both public and private operators in decisions about the organization of cycle logistics facilities, such as the location of urban consolidation centres or the composition of cycle fleets.

Spontaneous Cirrhosis Regression in an IFN-beta-induced AIH-like Syndrome Following Drug Withdrawal: Art of Facts or Artifacts?

Autoimmune hepatitis (AIH) is a disease of unknown aetiology with drug-induced AIH being the most complex and not fully understood type. We present the case of a 57-year-old female patient with acute icteric hepatitis after interferon-beta-1b (IFNβ-1b) administration for multiple sclerosis (MS). Based on liver autoimmune serology, histology and appropriate exclusion of other liver diseases, a diagnosis of AIH-related cirrhosis was established. Following discontinuation of IFNβ-1b, a complete resolution of biochemical activity indices was observed and the patient remained untreated on her own decision. However, 3 years later, after a course of intravenous methylprednisolone for MS, a new acute transaminase flare was recorded which subsided again spontaneously after 3 weeks. Liver biopsy and elastography showed significant fibrosis regression (F2 fibrosis). To our knowledge, this is the first report showing spontaneous cirrhosis regression in an IFNβ-1b-induced AIH-like syndrome following drug withdrawal, suggesting that cirrhosis might be reversible if the offending fibrogenic stimulus is withdrawn.

Explaining dinophysis cf. acuminata abundance in Antifer (Normandy, France) using dynamic linear regression

Classical regression analysis can be used to model time series. However, the assumption that model parameters are constant over time is not necessarily adapted to the data. In phytoplankton ecology, the relevance of time-varying parameter values has been shown using a dynamic linear regression model (DLRM). DLRMs, belonging to the class of Bayesian dynamic models, assume the existence of a non-observable time series of model parameters, which are estimated on-line, i.e. after each observation. The aim of this paper was to show how DLRM results could be used to explain variation of a time series of phytoplankton abundance. We applied DLRM to daily concentrations of Dinophysis cf. acuminata, determined in Antifer harbour (French coast of the English Channel), along with physical and chemical covariates (e.g. wind velocity, nutrient concentrations). A single model was built using 1989 and 1990 data, and then applied separately to each year. Equivalent static regression models were investigated for the purpose of comparison. Results showed that most of the Dinophysis cf. acuminata concentration variability was explained by the configuration of the sampling site, the wind regime and tide residual flow. Moreover, the relationships of these factors with the concentration of the microalga varied with time, a fact that could not be detected with static regression. Application of dynamic models to phytoplankton time series, especially in a monitoring context, is discussed.

Integration of Social Concerns in Collaborative Logistics and Transportation Networks

Part 21: Mobility and Logistics

Forward - Green Virtual Enterprises and Their Breeding Environments: Sustainable Manufacturing, Logistics and Consumption

Part 9: Innovation Networks

Use of posterior predictive assessments to evaluate model fit in multilevel logistic regression

Assessing the fit of a model is an important final step in any statistical analysis, but this is not straightforward when complex discrete response models are used. Cross validation and posterior predictions have been suggested as methods to aid model criticism. In this paper a comparison is made between four methods of model predictive assessment in the context of a three level logistic regression model for clinical mastitis in dairy cattle; cross validation, a prediction using the full posterior predictive distribution and two “mixed” predictive methods that incorporate higher level random effects simulated from the underlying model distribution. Cross validation is considered a gold standard method but is computationally intensive and thus a comparison is made between posterior predictive assessments and cross validation. The analyses revealed that mixed prediction methods produced results close to cross validation whilst the full posterior predictive assessment gave predictions that were over-optimistic (closer to the observed disease rates) compared with cross validation. A mixed prediction method that simulated random effects from both higher levels was best at identifying the outlying level two (farm-year) units of interest. It is concluded that this mixed prediction method, simulating random effects from both higher levels, is straightforward and may be of value in model criticism of multilevel logistic regression, a technique commonly used for animal health data with a hierarchical structure.