Forest inventory information needs in Northwest Russia

This thesis applies the customer value hierarchy model to forestry in order to determine strategic options to enhance the value of LiDAR technology in Russian forestry. The study is conducted as a qualitative case study with semi-structured interviews as a main source of the primary data. The customer value hierarchy model constitutes a theoretical base for the research. Secondary data incorporates information on forest resource management, LiDAR technology and Russian forestry. The model is operationalised using forestry literature and forms a basis for analyses of primary data. Analyses of primary data coupled with comprehension of Russian forest inventory system and knowledge on global forest inventory have led to conclusions on the forest inventory methods selection criteria and the organizations that would benefit the most from LiDAR technology use. The thesis recommends strategic options for LiDAR technology’s value enhancement in Russian forestry.

Proteomic inventory of myocardial proteins from patients with chronic Chagas' cardiomyopathy

Chronic Chagas' disease cardiomyopathy (CCC) is an often fatal outcome of Trypanosoma cruzi infection, with a poorer prognosis than other cardiomyopathies. CCC is refractory to heart failure treatments, and is the major indication of heart transplantation in Latin America. A diffuse myocarditis, plus intense myocardial hypertrophy, damage and fibrosis, in the presence of very few T. cruzi forms, are the histopathological hallmarks of CCC. To gain a better understanding of the pathophysiology of CCC, we analyzed the protein profile in the affected CCC myocardium. Homogenates from left ventricular myocardial samples of end-stage CCC hearts explanted during heart transplantation were subjected to two-dimensional electrophoresis with Coomassie blue staining; protein identification was performed by MALDI-ToF mass spectrometry and peptide mass fingerprinting. The identification of selected proteins was confirmed by immunoblotting. We demonstrated that 246 proteins matched in gels from two CCC patients. They corresponded to 112 distinct proteins. Along with structural/contractile and metabolism proteins, we also identified proteins involved in apoptosis (caspase 8, caspase 2), immune system (T cell receptor ß chain, granzyme A, HLA class I) and stress processes (heat shock proteins, superoxide dismutases, and other oxidative stress proteins). Proteins involved in cell signaling and transcriptional factors were also identified. The identification of caspases and oxidative stress proteins suggests the occurrence of active apoptosis and significant oxidative stress in CCC myocardium. These results generated an inventory of myocardial proteins in CCC that should contribute to the generation of hypothesis-driven experiments designed on the basis of the classes of proteins identified here.

Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China

The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regression models. The ANN model was tested against actual outcomes of an intertrochanteric femoral fracture database in China. The ANN model was generated with eight clinical inputs and a single output. ANN's performance was compared with a logistic regression model created with the same inputs in terms of accuracy, sensitivity, specificity, and discriminability. The study population was composed of 2150 patients (679 males and 1471 females): 1432 in the training group and 718 new patients in the testing group. The ANN model that had eight neurons in the hidden layer had the highest accuracies among the four ANN models: 92.46 and 85.79% in both training and testing datasets, respectively. The areas under the receiver operating characteristic curves of the automatically selected ANN model for both datasets were 0.901 (95%CI=0.814-0.988) and 0.869 (95%CI=0.748-0.990), higher than the 0.745 (95%CI=0.612-0.879) and 0.728 (95%CI=0.595-0.862) of the logistic regression model. The ANN model can be used for predicting 1-year mortality in elderly patients with intertrochanteric fractures. It outperformed a logistic regression on multiple performance measures when given the same variables.

Transduction motif analysis of gastric cancer based on a human signaling network

To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the mining of gastric cancer-related motifs in a network with three vertices. The significant motif difference method was adopted to identify significantly different motifs in the normal and cancer states. Finally, we conducted a series of analyses of the significantly different motifs, including gene ontology, function annotation of genes, and model classification. A human signaling network was constructed, with 1643 nodes and 5089 regulating interactions. The network was configured to have the characteristics of other biological networks. There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores. Genes in significantly different motifs were mainly enriched in functions associated with cancer genesis, such as regulation of cell death, amino acid phosphorylation of proteins, and intracellular signaling cascades. The top five significantly different motifs were mainly cascade and positive feedback types. Almost all genes in the five motifs were cancer related, including EPOR,MAPK14, BCL2L1, KRT18,PTPN6, CASP3, TGFBR2,AR, and CASP7. The development of cancer might be curbed by inhibiting signal transductions upstream and downstream of the selected motifs.

HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.

The role of network competence and international business competence in multinational corporations: Subsidiary perspective

On-going process of globalization makes companies all over the world to go beyond the national markets and internationalize. Organizational form of multinational corporation (MNC) has capabilities for establishing the affiliate companies in several countries. Thus, the relocation of resources occurs and particularly, the cross-border transfer of knowledge which possesses the competitive advantage. However, differences in countries` business environments and cultures may constrain this capability. The research aim of this thesis is to investigate the role of subsidiary’s network competence (ability to build and manage the relationships with other local business units) and international business competence in relation to the benefits that MNC receives from a subsidiary. Additionally, subsidiary’s business adaptation, partnerships and knowledge transfer mechanism with parent company and external partners are investigated. This research, conducted in the Finnish-Russian context, consists of theoretical and empirical parts. The qualitative approach in the form of multiple case studies is employed. The empirical data incorporated primary and secondary data in the form of interviews collected in 2013 and 2015 years. Interviews were collected from four Finnish case companies in Saint-Petersburg and Kaluga region and five Russian partner companies. Results are drawn from two cases from Saint-Petersburg. The abductive research approach for the results analysis is adopted. The results indicate that both competencies lead to the subsidiary’s local embeddedness in the form of mutual business activities with local business partners and product adaptation for the local market needs. In addition to the monetary benefits in form of payments or turnover share, local embeddedness brings the knowledge of the local environment which is utilized by an MNC in the long-term planning. Another found tacit benefit is the access to the national market. This is strategically useful benefit not only for parent MNC but also for the subsidiary’s partners, i.e. international suppliers.

Forest inventory information needs in Northwest Russia

This research report applies the customer value hierarchy model to forestry in order to determine strategic options to enhance the value of LiDAR technology in Russian forestry. The study is conducted as a qualitative case study with semi-structured interviews as a main source of the primary data. The customer value hierarchy model constitutes a theoretical base for the research. Secondary data incorporates information on forest resource management, LiDAR technology and Russian forestry. The model is operationalised using forestry literature and forms a basis for analyses of primary data. Analyses of primary data coupled with comprehension of Russian forest inventory system and knowledge on global forest inventory have led to conclusions on the forest inventory methods selection criteria and the organizations that would benefit the most from LiDAR technology use. The report recommends strategic options for LiDAR technology’s value enhancement in Russian forestry. This work has been conducted as a part of the project ‘Finnish-Russian Forest Academy 2 - Exploiting and Piloting’, which has been supported financially by the South-East Finland- Russia ENPI CBC 2007-2014 Programme.

Requisites for a successful implementation of an automated inventory replenishment system

Tutkimuksen tavoitteena oli selvittää automaattisten tilausjärjestelmien onnistuneen käyttöönottoon taustalla vaikuttavia tekijöitä vähittäiskaupan toimialalla ja etsiä ratkaisua kyseisten järjestelmien onnistuneeseen käyttöönottoon tässä ympäristössä. Tutkimus analysoi yli sadan kaupan järjestelmän käyttöönottoa ja käyttöönoton tuloksia. Tutkimusta varten haastateltiin niin yhtiön sisältä kuin ulkopuoleltakin mukana olleita hankintajärjestelmän ja jalkautuksen asiantuntijoita. Tämän lisäksi järjestelmän käyttöönottaneisiin kauppoihin lähetettiin kyselyt, joita analysoitiin ryhmissä automaattisen tilausjärjestelmän tietojen pohjalta. Työn tuloksena pystyttiin tunnistamaan tietty joukko taustatekijöitä, jotka tulee ottaa käyttöönotossa huomioon sekä saatuihin tutkimustuloksiin perustuen kehitettiin malli vastaavanlaisten järjestelmien käyttöönotolle vähittäiskaupan alalle.

The transforming network of a foreign company operating in Mongolia. Case: A Finnish firm in Mongolia

In the globalising business environment ever fewer market areas remain unknown. Mongolia is yet only considered as an isolated strip between two power states. The purpose of this study is to put Mongolia on the map of academic business research. This is done by describing the transforming network of a foreign company operating in Mongolia. The objective of the study is approached through a case study, which presents the transformation of a Finnish company operating in Mongolia. This study aims at providing understanding on how the foreign case company observes the transformations of its network. The transformation within the case company is reflected to the transformations that occur in the Mongolian business environment. This study was conducted through a qualitative, intrinsic case study approach. The empirical data was gathered by using the method of network pictures. The network pictures were completed with the assistance of themed interviews. In order to be able to analyse the transformation within a network, three different time periods were observed: the past period around 2000, the present around 2014, and the estimated future around 2020. The data was collected from four executives positioned either in Finland, Russia or Mongolia. The respondents have a long experience within the case company, they hold managerial position, and therefore were able to offer valuable data for this study. The analytical framework used to analyse the collected data was built on the industrial network model, the ARA (actors-resources-activities)-model. The study shows that the changing business environment of Mongolia was utilised by the case company. In order to better meet the transforming customer wishes, the case company transformed from being a retailer to being a manufacturer. The case company was able to become a pioneer in the market. Thus, the case company has undergone similar kind of rapid transformation as the economy of Mongolia in entirety. This study shows that the general nature of the ARA-model makes it usable for new research contexts. The initial ARA-model offers a way to identify the dimensions of a network and a mean to understand these dimensions. The ARA-model can be applied to different contexts and to all time dimensions, past, present and future. The managerial recommendations offered in this study are directed towards the managers that plan to start operations in Mongolia. While this study is the first of its kind, it offers a good starting point for the future research on the change of Mongolian business networks. Valuable information could, for example, be obtained from a comparative study between the case company of this study and a multinational mining company operating in Mongolia.

Optimizing the Performance of a Heat Exchanger Network

This research is the continuation and a joint work with a master thesis that has been done in this department recently by Hemamali Chathurangani Yashika Jayathunga. The mathematical system of the equations in the designed Heat Exchanger Network synthesis has been extended by adding a number of equipment; such as heat exchangers, mixers and dividers. The solutions of the system is obtained and the optimal setting of the valves (Each divider contains a valve) is calculated by introducing grid-based optimization. Finding the best position of the valves will lead to maximization of the transferred heat in the hot stream and minimization of the pressure drop in the cold stream. The aim of the following thesis will be achieved by practicing the cost optimization to model an optimized network.