“Eco-innovations in more sustainable supply chains for a low-carbon economy: A multiple case study of human critical success factors in Brazilian leading companies”

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Challenges of modeling depth-integrated marine primary productivity over multiple decades: A case study at BATS and HOT

The performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models (BOGCMs)) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ (14)C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades. Specifically, skill was assessed based on the models' ability to estimate the observed mean, variability, and trends of NPP. At both sites, more than 90% of the models underestimated mean NPP, with the average bias of the BOGCMs being nearly twice that of the ocean color models. However, the difference in overall skill between the best BOGCM and the best ocean color model at each site was not significant. Between 1989 and 2007, in situ NPP at BATS and HOT increased by an average of nearly 2% per year and was positively correlated to the North Pacific Gyre Oscillation index. The majority of ocean color models produced in situ NPP trends that were closer to the observed trends when chlorophyll-alpha was derived from high-performance liquid chromatography (HPLC), rather than fluorometric or SeaWiFS data. However, this was a function of time such that average trend magnitude was more accurately estimated over longer time periods. Among BOGCMs, only two individual models successfully produced an increasing NPP trend (one model at each site). We caution against the use of models to assess multiannual changes in NPP over short time periods. Ocean color model estimates of NPP trends could improve if more high quality HPLC chlorophyll-alpha time series were available.

Coordinated views to assist exploration of spatio-temporal data: a case study

In this paper we focus on providing coordinated visual strategies to assist users in performing tasks driven by the presence of temporal and spatial attributes. We introduce temporal visualization techniques targeted at such tasks, and illustrate their use with an application involving a climate classification process. The climate classification requires extensive Processing of a database containing daily rain precipitation values collected along over fifty years at several spatial locations in the São Paulo state, Brazil. We identify user exploration tasks typically conducted as part of the data preparation required in this process, and then describe how such tasks may be assisted by the multiple visual techniques provided. Issues related to the use of the multiple techniques by an end-user are also discussed.

Gorlin-Goltz Syndrome and Neoplasms: A Case Study

Gorlin syndrome is a rare autosomal dominant disorder exhibiting high penetrance and variable expressivity. It is characterized by facial dysmorphism, skeletal anomalies, multiple basal cell carcinomas, odontogenic keratocysts (OKC), palmar and plantar pits, bifid ribs, vertebral anomalies and a variety of other malformations. Various neoplasms', such as medulloblastomas, meningiomas, ovarian and cardiac fibromas are also found in this syndrome. Objective: To describe a twelve-year-old patient with Gorlin-Goltz syndrome, with basal cell carcinomas and promyelocytic leukemia developed after receiving craniospinal radiation for a medulloblastoma. Mild ribs as well as mandibular and maxillar OKC were also diagnosed. Conclusion: The patient with Gorlin-Goltz syndrome should receive close follow-up for early detection of malformations and malignant neoplasias.

Measuring the efficiency of outsourcing: An illustrative case study from the aerospace industry

Outsourcing is related to the action which an organization deals with its suppliers through a kind of business contract where a specific activity or service has been hired to be made. The outsourcing of some activities has become a common practice in the industry, nowadays. It reduces costs, significantly, in the production process and, at the same time, adds some values to the business organization. However it is necessary to measure the performance of these activities. Data Envelopment Analysis (DEA) is a non-parametric method useful to measure comparative performance. It has a wide range of applications measuring comparative efficiency. The Analytic Hierarchy Process (AHP) is a multiple criteria decision-making method that uses hierarchic structures to represent a decision problem and then develops priorities for the alternatives based on the decision-maker's judgments. This paper presents an integrated application based on DEA and AHP to evaluate the efficiency of subcontracted companies in a Brazilian aerospace factory. © 2007 Springer-Verlag London Limited.