Supplier segmentation and development in project business

The purpose of this study was to expand the applicability of supplier segmentation and development approaches to the project-driven construction industry. These practices are less exploited and not well documented in this operational environment compared to the process-centric manufacturing industry. At first, portfolio models to supply base segmentation and various supplier development efforts were investigated in literature review. A step-wise framework was structured for the empirical research. The empirical study employed multiple research methods in three case studies in a large Finnish construction company. The first study categorized the construction item classes into the purchasing portfolio and positioned suppliers to the power matrix by investigating buyer-supplier relations. Using statistical tests, the study also identified factors that affect suppliers’ performance. The final case study identified improvement areas of the interface between a main contractor and one if its largest suppliers. The final results indicate that only by assessing the supply base in a holistic manner and the power circumstances in it, buyers comprehend how to best establish appropriate supplier development strategies in the project environment.

Visual analytics for behavioral and niche market segmentation

Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.

A DNA enzyme targeting Egr-1 inhibits rat vascular smooth muscle cell proliferation by down-regulation of cyclin D1 and TGF-β1

We have demonstrated that a synthetic DNA enzyme targeting early growth response factor-1 (Egr-1) can inhibit neointimal hyperplasia following vascular injury. However, the detailed mechanism of this inhibition is not known. Thus, the objective of the present study was to further investigate potential inhibitory mechanisms. Catalytic DNA (ED5) and scrambled control DNA enzyme (ED5SCR) were synthesized and transfected into primary cultures of rat vascular smooth muscle cells (VSMCs). VSMC proliferation and DNA synthesis were analyzed by the MTT method and BrdU staining, respectively. Egr-1, TGF-β1, p53, p21, Bax, and cyclin D1 expression was detected by RT-PCR and Western blot. Apoptosis and cell cycle assays were performed by FACS. Green fluorescence could be seen localized in the cytoplasm of 70.6 ± 1.52 and 72 ± 2.73% VSMCs 24 h after transfection of FITC-labeled ED5 and ED5SCR, respectively. We found that transfection with ED5 significantly inhibited cultured VSMC proliferation in vitro after 24, 48, and 72 h of serum stimulation, and also effectively decreased the uptake of BrdU by VSMC. ED5 specifically reduced serum-induced Egr-1 expression in VSMCs, further down-regulated the expression of cyclin D1 and TGF-β1, and arrested the cells at G0/G1, inhibiting entry into the S phase. FACS analysis indicated that there was no significant difference in the rate of apoptosis between ED5- and ED5SCR-transfected cells. Thus, ED5 can specifically inhibit Egr-1 expression, and probably inhibits VSMC proliferation by down-regulating the expressions of cyclin D1 and TGF-β1. However, ED5 has no effect on VSMC apoptosis.

Gene expression promoted by the SV40 DNA targeting sequence and the hypoxia-responsive element under normoxia and hypoxia

The main objective of the present study was to find suitable DNA-targeting sequences (DTS) for the construction of plasmid vectors to be used to treat ischemic diseases. The well-known Simian virus 40 nuclear DTS (SV40-DTS) and hypoxia-responsive element (HRE) sequences were used to construct plasmid vectors to express the human vascular endothelial growth factor gene (hVEGF). The rate of plasmid nuclear transport and consequent gene expression under normoxia (20% O2) and hypoxia (less than 5% O2) were determined. Plasmids containing the SV40-DTS or HRE sequences were constructed and used to transfect the A293T cell line (a human embryonic kidney cell line) in vitro and mouse skeletal muscle cells in vivo. Plasmid transport to the nucleus was monitored by real-time PCR, and the expression level of the hVEGF gene was measured by ELISA. The in vitro nuclear transport efficiency of the SV40-DTS plasmid was about 50% lower under hypoxia, while the HRE plasmid was about 50% higher under hypoxia. Quantitation of reporter gene expression in vitro and in vivo, under hypoxia and normoxia, confirmed that the SV40-DTS plasmid functioned better under normoxia, while the HRE plasmid was superior under hypoxia. These results indicate that the efficiency of gene expression by plasmids containing DNA binding sequences is affected by the concentration of oxygen in the medium.

Adenovirus-mediated siRNA targeting TNF-α and overexpression of bone morphogenetic protein-2 promotes early osteoblast differentiation on a cell model of Ti particle-induced inflammatory response in vitro

Wear particles are phagocytosed by macrophages and other inflammatory cells, resulting in cellular activation and release of proinflammatory factors, which cause periprosthetic osteolysis and subsequent aseptic loosening, the most common causes of total joint arthroplasty failure. During this pathological process, tumor necrosis factor-alpha (TNF-α) plays an important role in wear-particle-induced osteolysis. In this study, recombination adenovirus (Ad) vectors carrying both target genes [TNF-α small interfering RNA (TNF-α-siRNA) and bone morphogenetic protein 2 (BMP-2)] were synthesized and transfected into RAW264.7 macrophages and pro-osteoblastic MC3T3-E1 cells, respectively. The target gene BMP-2, expressed on pro-osteoblastic MC3T3-E1 cells and silenced by the TNF-α gene on cells, was treated with titanium (Ti) particles that were assessed by real-time PCR and Western blot. We showed that recombinant adenovirus (Ad-siTNFα-BMP-2) can induce osteoblast differentiation when treated with conditioned medium (CM) containing RAW264.7 macrophages challenged with a combination of Ti particles and Ad-siTNFα-BMP-2 (Ti-ad CM) assessed by alkaline phosphatase activity. The receptor activator of nuclear factor-κB ligand was downregulated in pro-osteoblastic MC3T3-E1 cells treated with Ti-ad CM in comparison with conditioned medium of RAW264.7 macrophages challenged with Ti particles (Ti CM). We suggest that Ad-siTNFα-BMP-2 induced osteoblast differentiation and inhibited osteoclastogenesis on a cell model of a Ti particle-induced inflammatory response, which may provide a novel approach for the treatment of periprosthetic osteolysis.

Physical and chemical characterization of the pulp of different varieties of avocado targeting oil extraction potential

The aim of this study was to evaluate the physicochemical properties of avocado pulp of four different varieties (Avocado, Guatemala, Dickinson, and Butter pear) and to identify which has the greatest potential for oil extraction. Fresh avocado pulp was characterized by moisture, protein, fat, ash, carbohydrates and energy contents were determined. The carotenoids and chlorophyll contents were determined by the organic solvent extraction method. The results showed significant differences in the composition of the fruit when varieties are compared. However, the striking feature in all varieties is high lipid content; Avocado and Dickinson are the most suitable varieties for oil extraction, taking into account moisture content and the levels of lipids in the pulp. Moreover, it could be said that the variety Dickinson is the most affected by the parameters evaluated in terms of overall quality. Chlorophyll and carotenoids, fat-soluble pigments, showed a negative correlation with respect to lipids since it could be related to its function in the fruit. The varieties Avocado and Dickinson are an alternative to oil extraction having great commercial potential to be exploited thus avoiding waste and increasing farmers’ income.

New ways to do business plans in multicultural organizations

Business plans are made when establishing new company or when organizations launch new product or services. In this Master Thesis was examined the elements are included in the business plan and emphasized. Business plan is a wide document and can also contain company specific information, the literature review was restricted into three areas which were investigated from the relating literature and articles. The selected areas were Market Segmentation and Targeting, Competitive Environment, and Market Positioning and Strategy. The different business plan models were investigated by interviewing companies who operates in a different industry sectors from each other’s. The models were compared to each other and to the findings from literature. Based on interview results and literature findings, the business plan for fibre based packaging. The created business plan contains three selected areas. It was found that the selected business plan elements can be found from the interviewed companies’ business plans. The market segmentation was done by comparing the market share to known total market size. When analyzing the competitive environment, there was no one selected model in use. The tools to evaluate competitive environment was selected parts from both SWOT analysis and Porter’s five forces model in applicable part. Based on interview results, it can be state that the company or organization should find and built its own model for business plans. In order to receive the benefits for future planning, the company should use the same model for long time.

Visual Customer Segmentation and Data Exploration with the Self-Organizing Map

Advancements in information technology have made it possible for organizations to gather and store vast amounts of data of their customers. Information stored in databases can be highly valuable for organizations. However, analyzing large databases has proven to be difficult in practice. For companies in the retail industry, customer intelligence can be used to identify profitable customers, their characteristics, and behavior. By clustering customers into homogeneous groups, companies can more effectively manage their customer base and target profitable customer segments. This thesis will study the use of the self-organizing map (SOM) as a method for analyzing large customer datasets, clustering customers, and discovering information about customer behavior. Aim of the thesis is to find out whether the SOM could be a practical tool for retail companies to analyze their customer data.

Uncertainties, monetary policy and financial stability: challenges on inflation targeting

This work aims at presenting the challenges that inflation targeting central banks may face since uncertainties represent a harmful element for the effectiveness of monetary policy, and since financial instabilities may disturb the transmission mechanisms - in particular, the expectation channel - and thus the economic stability. Financial stability must not be considered as a simple goal of monetary policy, but a precondition for central banks operate their policies and reach the goals of inflation and output stability. The work identifies different sources of uncertainties that surround central banks' decisions; and approaches the role that inflation targeting central banks should play according to some basic principles that can serve as useful guides for central banks to help them achieve successful outcomes in their conduct of monetary policy.

Probing MST1 Kinase Sequence and Structure for Rational Drug Discovery (Targeting diabetes by blocking protein-protein interactions)

Apoptotic beta cell death is an underlying cause majorly for type I and to a lesser extent for type II diabetes. Recently, MST1 kinase was identified as a key apoptotic agent in diabetic condition. In this study, I have examined MST1 and closely related kinases namely, MST2, MST3 and MST4, aiming to tackle diabetes by exploring ways to selectively block MST1 kinase activity. The first investigation was directed towards evaluating possibilities of selectively blocking the ATP binding site of MST1 kinase that is essential for the activity of the enzymes. Structure and sequence analyses of this site however revealed a near absolute conservation between the MSTs and very few changes with other kinases. The observed residue variations also displayed similar physicochemical properties making it hard for selective inhibition of the enzyme. Second, possibilities for allosteric inhibition of the enzyme were evaluated. Analysis of the recognized allosteric site also posed the same problem as the MSTs shared almost all of the same residues. The third analysis was made on the SARAH domain, which is required for the dimerization and activation of MST1 and MST2 kinases. MST3 and MST4 lack this domain, hence selectivity against these two kinases can be achieved. Other proteins with SARAH domains such as the RASSF proteins were also examined. Their interaction with the MST1 SARAH domain were evaluated to mimic their binding pattern and design a peptide inhibitor that interferes with MST1 SARAH dimerization. In molecular simulations the RASSF5 SARAH domain was shown to strongly interact with the MST1 SARAH domain and possibly preventing MST1 SARAH dimerization. Based on this, the peptidic inhibitor was suggested to be based on the sequence of RASSF5 SARAH domain. Since the MST2 kinase also interacts with RASSF5 SARAH domain, absolute selectivity might not be achieved.

Melanosomal targeting sequences from gp100 are essential for MHC class II-restricted endogenous epitope presentation and mobilization to endosomal compartments

CD4+ T lymphocytes play an important role in CD8+ T cell-mediated responses against tumors. Considering that about 20% of melanomas express major histocompatibility complex (MHC) class II, it is plausible that concomitant antigenic presentation by MHC class I and class II complexes shapes positive (helper T cells) or negative (regulatory T cells) anti-tumor responses. Interestingly, gp100, a melanoma antigen, can be presented by both MHC class I and class II when expressed endogenously, suggesting that it can reach endosomal/MHC class II compartments (MIIC). Here, we demonstrated that the gp100 putative amino-terminal signal sequence and the last 70 residues in carboxy-terminus, are essential for MIIC localization and MHC class II presentation. Confocal microscopy analyses confirmed that gp100 was localized in LAMP-1+ endosomal/MIIC. Gp100-targeting sequences were characterized by deleting different sections in the carboxy-terminus (residues 590 to 661). Transfection in 293T cells, expressing MHC class I and class II molecules, revealed that specific deletions in carboxy-terminus resulted in decreased MHC class II presentation, without effects on MHC class I presentation, suggesting a role in MIIC trafficking for these deleted sections. Then, we used these gp100-targeting sequences to mobilize the green fluorescent protein (GFP) to endosomal compartments, and to allow MHC class II and class I presentation of minimal endogenous epitopes. Thus, we concluded that these specific sequences are MIIC targeting motifs. Consequently, these sequences could be included in expression cassettes for endogenously expressed tumor or viral antigens to promote MHC class II and class I presentation and optimize in vivo T cell responses, or as an in vitro tool for characterization of new MHC class II epitopes.

Semiautomated 3D liver segmentation using computed tomography and magnetic resonance imaging

Le foie est un organe vital ayant une capacité de régénération exceptionnelle et un rôle crucial dans le fonctionnement de l’organisme. L’évaluation du volume du foie est un outil important pouvant être utilisé comme marqueur biologique de sévérité de maladies hépatiques. La volumétrie du foie est indiquée avant les hépatectomies majeures, l’embolisation de la veine porte et la transplantation. La méthode la plus répandue sur la base d'examens de tomodensitométrie (TDM) et d'imagerie par résonance magnétique (IRM) consiste à délimiter le contour du foie sur plusieurs coupes consécutives, un processus appelé la «segmentation». Nous présentons la conception et la stratégie de validation pour une méthode de segmentation semi-automatisée développée à notre institution. Notre méthode représente une approche basée sur un modèle utilisant l’interpolation variationnelle de forme ainsi que l’optimisation de maillages de Laplace. La méthode a été conçue afin d’être compatible avec la TDM ainsi que l' IRM. Nous avons évalué la répétabilité, la fiabilité ainsi que l’efficacité de notre méthode semi-automatisée de segmentation avec deux études transversales conçues rétrospectivement. Les résultats de nos études de validation suggèrent que la méthode de segmentation confère une fiabilité et répétabilité comparables à la segmentation manuelle. De plus, cette méthode diminue de façon significative le temps d’interaction, la rendant ainsi adaptée à la pratique clinique courante. D’autres études pourraient incorporer la volumétrie afin de déterminer des marqueurs biologiques de maladie hépatique basés sur le volume tels que la présence de stéatose, de fer, ou encore la mesure de fibrose par unité de volume.

Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods

The work is intended to study the following important aspects of document image processing and develop new methods. (1) Segmentation ofdocument images using adaptive interval valued neuro-fuzzy method. (2) Improving the segmentation procedure using Simulated Annealing technique. (3) Development of optimized compression algorithms using Genetic Algorithm and parallel Genetic Algorithm (4) Feature extraction of document images (5) Development of IV fuzzy rules. This work also helps for feature extraction and foreground and background identification. The proposed work incorporates Evolutionary and hybrid methods for segmentation and compression of document images. A study of different neural networks used in image processing, the study of developments in the area of fuzzy logic etc is carried out in this work

Motion Segmentation And Meanshift Assisted Contour Refinement For Airborne Video

This paper presents methods for moving object detection in airborne video surveillance. The motion segmentation in the above scenario is usually difficult because of small size of the object, motion of camera, and inconsistency in detected object shape etc. Here we present a motion segmentation system for moving camera video, based on background subtraction. An adaptive background building is used to take advantage of creation of background based on most recent frame. Our proposed system suggests CPU efficient alternative for conventional batch processing based background subtraction systems. We further refine the segmented motion by meanshift based mode association.

A semi-automatic method for segmentation and 3D modeling of glioma tumors from brain MRI

This work presents an efficient method for volume rendering of glioma tumors from segmented 2D MRI Datasets with user interactive control, by replacing manual segmentation required in the state of art methods. The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the pre- operative tumor volume is essential. Tumor portions were automatically segmented from 2D MR images using morphological filtering techniques. These seg- mented tumor slices were propagated and modeled with the software package. The 3D modeled tumor consists of gray level values of the original image with exact tumor boundary. Axial slices of FLAIR and T2 weighted images were used for extracting tumors. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming proc- ess and is prone to error. These defects are overcome in this method. Authors verified the performance of our method on several sets of MRI scans. The 3D modeling was also done using segmented 2D slices with the help of a medical software package called 3D DOCTOR for verification purposes. The results were validated with the ground truth models by the Radi- ologist.