Improving the environmental performance of bedding products by using life cycle assessment at the design stage

Improvement of the environmental performance of processes and products is a common objective in industry, and has been receiving increased attention in recent years. The main objective of this work is to evaluate the potential environmental impact of two bedding products, a polyurethane foam mattress (PFM) and a pocket spring mattress (PSM). These two types are the most common mattresses used in Europe. A Life Cycle Assessment (LCA) shows that the PFM has a higher environmental impact than the PSM. For both products the main cause of environmental impact is the manufacturing process, respectively the polyurethane foam block moulding process for the PFM, and the pocket spring nucleus process for the PSM. A scenario analysis shows the possibility of reducing the environmental impact of the products’ life cycle using an alternative End-of-Life scenario, resorting to incineration rather than landfill. Two strategies were also studied in order to reduce the environmental impact of the PFM: (1) reutilization of foam that was sent to the waste system management, and (2) a 20% weight reduction of the polyurethane foam. The second strategy has proven to be the most effective.

Fatigue Prediction on Fibrin Poly-ε-caprolactone Macroporous Scaffolds

Tissue engineering applications rely on scaffolds that during its service life, either for in-vivo or in vitro applications, are under mechanical solicitations. The variation of the mechanical condition of the scaffold is strongly relevant for cell culture and has been scarcely addressed. Fatigue life cycle of poly-ε-caprolactone, PCL, scaffolds with and without fibrin as filler of the pore structure were characterized both dry and immersed in liquid water. It is observed that the there is a strong increase from 100 to 500 in the number of loading cycles before collapse in the samples tested in immersed conditions due to the more uniform stress distributions within the samples, the fibrin loading playing a minor role in the mechanical performance of the scaffolds

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Conceptual design of a conveyer system for supporting basic quality of life of bedridden elderly people

With the increasing number of aged people, especially in developed countries, Ambient Assisted Living solutions have become an important subject to be explored and developed. Currently, as specialized Institutions in geriatric care cannot cope with the increasing requests for support of quality of life, patients have to remain at their homes having as caregiver the other member of the couple or a member of close family. A solution for supporting the caregiver, during assisting the bedridden person with some basic tasks as eating, taking a bath and/or hygiene care is of utmost importance. This paper presents an approach for supporting the caregiver in moving and repositioning the bedridden elderly people (BEP) with the assistance of a mechanical system conveyer. The conceptual design of the mechanical system must be devoted to assist the caregiver in the handling and repositioning of the BEP. The proposed mechatronic system must, ideally, minimize the system's handling complexity, reduce the number of caregivers and the amount of spended and needed effort.

Conceptual design of a mechatronic system for supporting basic quality of life of bedridden elderly people

Ambient Assisted Living is an important subject to be explored and developed, especially in developed countries, due to the increasing number of aged people. In this context the development of mechatronic support systems for bedridden elderly people (BEP) living in their homes is essential in order to support independence, autonomy and improve their quality of life. Some basic tasks as eating, taking a bath and/or hygiene cares become difficult to execute, regarding that often the main caregiver is the other element of the aged couple (husband or wife). This paper presents the conceptual design of a mechanical system especially devoted to assist the caregiver in the handling and repositioning of the BEP. Issues as reducing the number of caregivers, to only one, and reducing the system's handling complexity (because most of the time it will be used by an aged person) are considered. The expertise obtained from the visits to rehabilitation centers and hospitals, and from working meetings, are considered in the development of the proposed mechatronic system.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Artificial neural networks for automatic modelling of the pectus excavatum corrective prosthesis

Pectus excavatum is the most common deformity of the thorax and usually comprises Computed Tomography (CT) examination for pre-operative diagnosis. Aiming at the elimination of the high amounts of CT radiation exposure, this work presents a new methodology for the replacement of CT by a laser scanner (radiation-free) in the treatment of pectus excavatum using personally modeled prosthesis. The complete elimination of CT involves the determination of ribs external outline, at the maximum sternum depression point for prosthesis placement, based on chest wall skin surface information, acquired by a laser scanner. The developed solution resorts to artificial neural networks trained with data vectors from 165 patients. Scaled Conjugate Gradient, Levenberg-Marquardt, Resilient Back propagation and One Step Secant gradient learning algorithms were used. The training procedure was performed using the soft tissue thicknesses, determined using image processing techniques that automatically segment the skin and rib cage. The developed solution was then used to determine the ribs outline in data from 20 patient scanners. Tests revealed that ribs position can be estimated with an average error of about 6.82±5.7 mm for the left and right side of the patient. Such an error range is well below current prosthesis manual modeling (11.7±4.01 mm) even without CT imagiology, indicating a considerable step forward towards CT replacement by a 3D scanner for prosthesis personalization.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Changes in the ways of life of farmers in the northwest of Portugal after 1980

ABSTRACT This study analyzes the changes from 1980s in the lifestyles of families of pluriactive and exclusively agricultural farmers in the northwest of Portugal caused by the income arising from the migration of at least one member of the family to another country in the European Union and the narrowing of the labor and consumer markets among the villages, towns and cities. The theoretical framework used to analyze the changes in the way of life of the pluriactive farmers was based on Giddens' theory of structuration, which denies both the absolute determinism of the structure on the subject and the freedom of unrestrained action of these same subjects. The study was carried out with the application of a survey to 78 farmers, divided into "pluriactive" and "exclusively agricultural" farmers. The findings pointed out to a greater aquisition of modes of urban life by pluriactive farmers compared with the exclusively agricultural farmers and showed a generational bias in this process of acculturation.

Applications of artificial intelligence to condition-based maintenance

In this paper we discuss interesting developments of expert systems for machine diagnosis and condition-based maintenance. We review some elements of condition-based maintenance and its applications, expert systems for machine diagnosis, and an example of machine diagnosis. In the last section we note some problems to be resolved so that expert systems for machine diagnosis may gain wider acceptance in the future.

Focusing illusion in satisfaction with life among college students living in Brazil

Literature shows that there are significant associations between health and happiness. Various countries are considering, contemplating or formally incorporating the happiness variable into their public health policies. Moreover, the private sector has shown interest in the topic. Based on that This article examines the biases in the perception of satisfaction with life among young adults in two Brazilian cities. The study explores the associations between aspects of life and perception of happiness because public policies associated with happiness require an improved understanding of the subjectivity of the sense of well-being. A survey conducted among 368 college students enabled analysis through Multivariate Analysis of Covariance (MANCOVA) and linear regression. The results suggest that, although there were no significant differences in general satisfaction with life between the two cities, there were indications of focusing illusion in the perception of happiness caused by expectations arising from the feeling of personal insecurity in a metropolis.

Continuing and life-long education for Social Work

Pretende defender que a educação contínua e ao longo da vida para o Serviço Social deve levar em conta os caminhos e as perspectivas que ultrapassam a arena da profissão do assistente social, e essa educação deve dialogar com os avanços nas vidas e nos trabalhos profissionais. Os assistentes sociais podem desta maneira moverem-se entre a prática, a gestão, a política profissional e a educação. Desde a experiência pré-qualificadora até à reforma, a avaliação e a supervisão podem ajudar a desenvolver caminhos profissionais e planos de educação relevantes. O exemplo deste processo de educação contínua multiprofissional em St. Christopher’s Hospice London pode ajudar a compreender como as pessoas podem desenvolver-se como pessoas e nos seus projectos profissionais.

Aspectos ecológicos da leishmaniose tegumentar americana: 2. ecótopo artificial como abrigo de Psychodopygus intermedius e observações sobre alimentação e reprodução sob influência de fatores físicos naturais

As observações levadas a cabo em um galinheiro experimental mostraram que Psychodopygus intermedius tem a capacidade de nele abrigar-se. Para se chegar a este resultado, a metodologia utilizada consistiu na coleta total diurna e exame do estado de alimentação e digestão sangüínea dos Ps. intermedius como parâmetro da sua maior ou menor permanência no ecótopo estudado. Além disso, observou-se paralelamente, os tempos para o repasto sangüíneo, digestão completa, oviposição, sobrevivência e cópula sob a influência direta dos fatores físicos naturais. A importância epidemiológica dos resultados reside em novas elucidações experimentais sobre a viabilidade da transmissão da leshmaniose tegumentar ocorrer em ambiente domiciliar.