Genetically Modified Organisms (GMOs) and Agroecology in Agricultural Production in the United States - A Comparative Analysis.

The world’s population is growing at a rapid rate and one of the primary problems of a growing is food supply. To ensure food supply and security, the biggest companies in the agricultural sector of the United States and all over the world have collaborated to produce genetically modified organisms, including crops, that have a tendency to increase yields and are speculated to reduce pesticide use. It’s a technology that is declared to have a multitude of benefits. During the same time period another set of practices has risen to the horizon by the name of agroecology. It spreads across many different sectors such as politics, sociology, environment, health and so on. Moreover, it involves primitive organic techniques that can be applied at farm level to enhance the performance of an ecosystem to effectively decrease the negative effect on environment and health of individuals while producing good quality foods. Since both the processes proclaim sustainable development, a natural question may come in mind that which one seems more favorable? During the course of this study, genetically modified organisms (GMOs) and agroecology are compared within the sphere of social, environmental and health aspects. The results derived upon a comparative analysis of scientific literature tend to prove that GMOs pose a greater threat to the environment, health of individuals and the generalized social balance in the United States compared to agroecological practices. Economic indicators were not included in the study and more studies might be needed in the future to get a broader view on the subject.

Modeling a Network of Heat Exchangers

This research work addresses the problem of building a mathematical model for the given system of heat exchangers and to determine the temperatures, pressures and velocities at the intermediate positions. Such model could be used in nding an optimal design for such a superstructure. To limit the size and computing time a reduced network model was used. The method can be generalized to larger network structures. A mathematical model which includes a system of non-linear equations has been built and solved according to the Newton-Raphson algorithm. The results obtained by the proposed mathematical model were compared with the results obtained by the Paterson approximation and Chen's Approximation. Results of this research work in collaboration with a current ongoing research at the department will optimize the valve positions and hence, minimize the pumping cost and maximize the heat transfer of the system of heat exchangers.

Blastocyst-endometrium interaction: intertwining a cytokine network

The successful implantation of the blastocyst depends on adequate interactions between the embryo and the uterus. The development of the embryo begins with the fertilized ovum, a single totipotent cell which undergoes mitosis and gives rise to a multicellular structure named blastocyst. At the same time, increasing concentrations of ovarian steroid hormones initiate a complex signaling cascade that stimulates the differentiation of endometrial stromal cells to decidual cells, preparing the uterus to lodge the embryo. Studies in humans and in other mammals have shown that cytokines and growth factors are produced by the pre-implantation embryo and cells of the reproductive tract; however, the interactions between these factors that converge for successful implantation are not well understood. This review focuses on the actions of interleukin-1, leukemia inhibitory factor, epidermal growth factor, heparin-binding epidermal growth factor, and vascular endothelial growth factor, and on the network of their interactions leading to early embryo development, peri-implantatory endometrial changes, embryo implantation and trophoblast differentiation. We also propose therapeutical approaches based on current knowledge on cytokine interactions.

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.

LISTERIA SPP., COLIFORMES TOTAIS E FECAIS E E.COLI NO LEITE CRU E PASTEURIZADO DE UMA INDÚSTRIA DE LATICÍNIOS, NO ESTADO DA PARAÍBA (BRASIL)

Investigou-se a qualidade microbiológica do leite in natura e na linha de produção (leite recém-pasteurizado e leite ensacado), de uma usina de beneficiamento em Campina Grande-PB. Foi pesquisada a presença de Listeria spp. e sua diversidade de espécies, os níveis de coliformes totais (CT), coliformes fecais (CF) e Escherichia coli. Analisou-se um total de 75 amostras de leite, sendo 45 de leite cru, 15 de leite recém-pasteurizado e 15 de leite ensacado. Os resultados foram reunidos em dois grupos segundo o período de monitoramento: antes e após mudanças no processo de higienização da usina. Foi evidenciada elevada contaminação nas amostras de leite cru nas duas épocas. Na primeira (março-abril/1998), todas as amostras de leite beneficiado estiveram fora dos padrões da legislação vigente para CT e CF; na segunda (maio-agosto/1998), houve acentuada redução dos níveis destas bactérias indicadoras, porém as melhorias na higienização não foram suficientes para solucionar este problema, visto que 11,1% das amostras recém-pasteurizadas estavam fora dos padrões para CT e 33,3% para CF. Das amostras ensacadas, 22,2% estavam fora dos padrões para CT e 44,4% para CF. Comparando-se os resultados de CT, CF, e E.coli nas amostras de leite recém-pasteurizado e não ensacado com as amostras de leite ensacado, foi verificado que as amostras após serem pasteurizadas e ensacadas apresentaram valores de CT e CF levemente mais elevados, sugerindo contaminação durante o processo de ensacamento ou falhas na armazenagem. Observou-se que 33 (73,3%) das amostras de leite cru e 9 (30%) das de leite pasteurizado estavam contaminadas com Listeria spp., sendo identificadas L. monocytogenes em 17 (51,5%) amostras de leite cru e em 9 (100%) de leite beneficiado (4 recém-pasteurizadas e 5 ensacadas). Em relação à diversidade de espécies, nas amostras de leite cru foram encontradas: L. monocytogenes (66,6%), L. innocua (25,3%), L. ivanovii (3,9%), L. welshimeri (2,5%) e L. grayi (1,5%). Nas amostras de leite pasteurizado isolaram-se: L. monocyogenes e L. innocua. O conjunto dos resultados evidenciou deficiências higiênico-sanitárias no leite in natura e ao longo do processo de produção, resultando em porcentagens elevadas de amostras que ultrapassaram os valores padrões de CT e CF além de apresentarem-se contaminadas por Listeria spp., com predominância de L. monocytogenes, sugerindo a existência de uma relação direta entre os altos índices de coliformes e a presença de Listeria spp.

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.

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.