Second primitive malignant tumour in patients with gynaecological cancer

OBJECTIVE: The purpose of this study was to characterise the occurrence of multiple primitive gynaecological malignant neoplasias, restricted to the genital tract and breast or associated with other organs, and to detect which types of association are most frequent concerning location, histology and staging. POPULATION AND METHODS: The records of patients with gynaecological cancer at the Portuguese Institute of Oncology--Lisbon Centre, between 1986 and 1993 were used in this study. RESULTS: Of the 10,746 women with gynaecological cancer, 91 (0.8%) were found to have a second primitive malignant neoplasia. Of these neoplasias, 64% (58 cases) were also located at a gynaecological site. The most frequent associations were endometrium/breast (13 cases), bilateral breast (12 cases) and ovary/endometrium (11 cases). The majority of primitive multiple gynaecological tumours were synchronous. Regarding gynaecological cancer and non-gynaecological cancer, in 28 cases (31%), the most common non-gynaecological location was the colon/rectum. Five patients had triple tumours. CONCLUSION: Although these situations are relatively rare the possibility of multiple primitive cancers should be considered with the presence of malignant tumours in two or more organs. This distinction between multiple primitive or metastatic cancers could be important for treatment as well as prognosis.     

SQL extension for spatio-temporal data

An SQL extension is formalized for the management of spatio-temporal data, i.e. of spatial data that evolves with respect to time. The extension is dedicated to applications such as topography, cartography, and cadastral systems, hence it considers discrete changes both in space and in time. It is based on the rigid formalization of data types and of SQL constructs. Data types are defined in terms of time and spatial quanta. The SQL constructs are defined in terms of a kernel of few relational algebra operations, composed of the well-known operations of the 1NF model and of two more, Unfold and Fold. In conjunction with previous work, it enables the uniform management of 1NF structures that may contain not only spatio-temporal but also either purely temporal or purely spatial or conventional data. The syntax and semantics of the extension is fully consistent with the {SQL:2003} standard.     

Qualitative and Quantitative Comparison of Plasma Exosomes from Neonates and Adults

Exosomes are extracellular vesicles that contain nucleic acids, lipids and metabolites, and play a critical role in health and disease as mediators of intercellular communication. The majority of extracellular vesicles in the blood are platelet-derived. Compared to adults, neonatal platelets are hyporeactive and show impaired granule release, associated with defects in Soluble N-ethylmaleimide-sensitive fusion Attachment protein REceptor (SNARE) proteins. Since these proteins participate in biogenesis of exosomes, we investigated the potential differences between newborn and adult plasma-derived exosomes. Plasma-derived exosomes were isolated by ultracentrifugation of umbilical cord blood from full-term neonates or peripheral blood from adults. Exosome characterization included size determination by transmission electron microscopy and quantitative proteomic analysis. Plasma-derived exosomes from neonates were significantly smaller and contained 65% less protein than those from adults. Remarkably, 131 proteins were found to be differentially expressed, 83 overexpressed and 48 underexpressed in neonatal (vs. adult) exosomes. Whereas the upregulated proteins in plasma exosomes from neonates are associated with platelet activation, coagulation and granule secretion, most of the underexpressed proteins are immunoglobulins. This is the first study showing that exosome size and content change with age. Our findings may contribute to elucidating the potential “developmental hemostatic mismatch risk” associated with transfusions containing plasma exosomes from adults.     

A functional approach for the formalization of the fixture design process

The design of machining fixtures is a highly complex process that relies on designer experience and his/her implicit knowledge to achieve a good design. In order to facilitate its automation by the development of a knowledge-based application, the explicit definition of the fixture design process and the knowledge involved is a prior and a fundamental task to undertake. Additionally, a fundamental and well-known engineering principle should be considered: the functional requirements and their associated constraints should be the first input to any design process. Considering these two main ideas, this paper presents the development undertaken to facilitate the automation of the fixture design process based on a functional approach.In this context, the MOKA methodology has been used to elicit fixtures knowledge. IDEF0 and UML have been used to represent the fixture design process. A methodology based on the function concept and aiming to formalize such design process is proposed. Fixture functional requirements have been defined and formalized. Functional fixtures elements have been used to create a functional design solution, the link of these elements with the functional requirements and with typical commercial fixture components has been defined via tables and rules mapping. And finally, a prototype knowledge-based application has been developed in order to make an initial validation of the proposed methodology.     

Neural Network and Classification Approach in Identifying Customer Behavior in the Banking Sector: A Case Study of an International Bank

The customer relationship focus for banks is in development of main competencies and strategies of building strong profitable customer relationships through considering and managing the customer impression, influence on the culture of the bank, satisfactory treatment, and assessment of valued relationship building. Artificial neural networks (ANNs) are used after data segmentation and classification, where the designed model register records into two class sets, that is, the training and testing sets. ANN predicts new customer behavior from previously observed customer behavior after executing the process of learning from existing data. This article proposes an ANN model, which is developed using a six‐step procedure. The back‐propagation algorithm is used to train the ANN by adjusting its weights to minimize the difference between the current ANN output and the desired output. An evaluation process is conducted to determine whether the ANN has learned how to perform. The training process is halted periodically, and its performance is tested until an acceptable result is obtained. The principles underlying detection software are grounded in classical statistical decision theory.     

Methodology for capturing and formalizing DFM Knowledge

Design for manufacturing (DFM) practices lead to more competitive products from the point of view of cost, development time and quality. However, the success of considering manufacturing issues during design process would be higher if manufacturing information was more readily available and designers needed less experience to select information relevant to DFM.     

The Early Bird Gets the Worm,But the Second Mouse Gets the Cheese: Non‐Technological Innovation in Creative Industries

In the context of economic turmoil, firms in the creative industries (CIs) must make fast decisions as to when to break through with innovations. This paper discusses non‐technological, organizational innovation of early‐adopters, first movers and early followers in order to overcome persistent economic decline, and the implication of different strategies for innovation success. The strategic principle of the pioneer's advantage rests on pre‐emption – the premise that ‘the early bird gets the worm’ and this often applies to business model innovation (BMI). ‘But the second mouse gets the cheese’ points at early followers who may have a more systematic, strategic approach towards innovation. Greater understanding of the advantages of each strategic approach and their significance for innovation performance is critical for CIs where unpredictability and the accelerating pace of change pervade the decisions concerning innovation. Drawing on five exemplary cases of archaeological firms in Spain, this paper explores different innovation process dynamics. The study develops a contingency model where pioneers who challenge their current business model, may be outperformed by early followers who incorporate complementary management innovation (MI) initiatives into the BMI.