Internal Logistics Process Improvement using PDCA: A Case Study in the Automotive Sector

Background: The Plan-do-check-act (PDCA) cycle methodology for a continuous improvement project implementation aims for the internal logistics upgrade, which is especially important in the industrial context of a component manufacturing company for the automotive sector. Objectives: The goal is to quantify the gains from waste reduction based on the usage of the PDCA cycle as a tool in the implementation and optimisation of a milk run in an assembly line of a company in the automotive sector by determining the optimal cycle time of supply and the standardisation of the logistic supply process and the materials’ flow. Methods/Approach: The research was conducted through observation and data collection in loco, involving two main phases: planning and implementation. According to the phases of the PDCA cycle, the process was analysed, and tools such as the SIPOC matrix, process stratification, 5S, and visual management were implemented. Results: Using Lean tools, it was possible to reduce waste by establishing concise flows and defining a supply pattern, which resulted in a reduction of movements. The transportation waste was reduced by fixing the position of more than half of the materials in the logistic trailers. The developed Excel simulator provided the logistic train\u27s optimal cycle time. Conclusions: The assembly line supplied by milk-run was fundamental to highlight a range of improvements in the process of internal supply, such as better integration of stock management systems, greater application of quality, or the adoption of better communication systems between the different areas and employees

Undernutrition and associated factors among hospitalized patients

Background & aims: The identification of modifiable risk factors associated with disease-related undernutrition at hospital admission will contribute to the development of integrated intervention and control strategies for a timely primary prevention. This study aim was to quantify the association between functional autonomy and undernutrition. Methods: A multicentric cross-sectional study was developed in six public hospitals in Portugal. Undernutrition risk was assessed using Nutritional Risk Screening 2002, undernutrition status was classified from anthropometry and functional autonomy was evaluated using the Katz Index. Results: In this sample of 1144 patients, 36% were at undernutrition risk and 9.7% undernourished. In logistic regression analysis, dependent patients were at an increased risk of undernutrition (OR ¼ 1.69, 95% confidence interval (CI) ¼ 1.20e2.39). The following parameters: illiteracy (OR ¼ 2.45, CI ¼ 1.52e3.96), age (one year increment) (OR ¼ 1.03, CI ¼ 1.02e1.04), male (OR ¼ 1.61, CI ¼ 1.19e2.16), single/divorced/widowed (OR ¼ 1.83, CI ¼ 1.34e2.51) and smoker (OR ¼ 1.55, CI ¼ 1.02e2.35) also increased the undernutrition risk. The impaired functional status, being single, divorced or widowed and be a smoker were also associated with anthropometric undernutrition. Conclusions: Functional impairment is related with undernutrition risk and with anthropometrical undernutrition at hospital admission. We also conclude that little extra information is gained by using anthropometrical indices compared to NRS 2002 when assessing the factors associated with undernutrition.info:eu-repo/semantics/publishedVersio

Image analysis as a tool for viability and recombinant protein production assessment during E. coli fermentations

The development of monitoring methods for physiological state assessment during recombinant fermentation processes has been encouraged by the need to evaluate the influence of processing conditions in recombinant protein production. In this work, microscopy and image analysis techniques were used for the quantification of viability and protein production in two recombinant E. coli batch fermentations. Images obtained from light microscopy with phase contrast were used to assess the total number of cells in a given sample and, from epifluorescence microscopy, both producing and dead cells were counted using two different filters. This methodology allowed the extraction of information related to cell viability and recombinant protein production. This information, combined with standard fermentation data, allowed the derivation of interesting hypothesis that can be used afterwards for experimental design and further validation. Additionally, the ratios calculated in this work can be complemented with other parameters that can be extracted from image analysis

Motility assessment of the ciliated tetrahymena pyriformis after exposition to toxic compounds using image analysis

PRAXIS XXI

Hybrid Speciation in a Marine Mammal: The Clymene Dolphin (Stenella clymene)

Natural hybridization may result in the exchange of genetic material between divergent lineages and even the formation of new taxa. Many of the Neo-Darwinian architects argued that, particularly for animal clades, natural hybridization was maladaptive. Recent evidence, however, has falsified this hypothesis, instead indicating that this process may lead to increased biodiversity through the formation of new species. Although such cases of hybrid speciation have been described in plants, fish and insects, they are considered exceptionally rare in mammals. Here we present evidence for a marine mammal, Stenella clymene, arising through natural hybridization. We found phylogenetic discordance between mitochondrial and nuclear markers, which, coupled with a pattern of transgressive segregation seen in the morphometric variation of some characters, support a case of hybrid speciation. S. clymene is currently genetically differentiated from its putative parental species, Stenella coerueloalba and Stenella longisrostris, although low levels of introgressive hybridization may be occurring. Although non-reticulate forms of evolution, such as incomplete lineage sorting, could explain our genetic results, we consider that the genetic and morphological evidence taken together argue more convincingly towards a case of hybrid speciation. We anticipate that our study will bring attention to this important aspect of reticulate evolution in non-model mammal species. The study of speciation through hybridization is an excellent opportunity to understand the mechanisms leading to speciation in the context of gene flow.info:eu-repo/semantics/publishedVersio

Cytotoxicity and antibacterial studies of iridoids and phenolic compounds isolated from the latex of Himatanthus sucuuba

The latex of Himatanthus sucuuba (Spruce) Woodson, used popularly in the Amazon for the treatment of tumors, gastritis, inflammations and infections, was evaluated for cytotoxicity and antibacterial activities. The iridoid lactones, plumericin and isoplumericin were isolated from latex by bioassay fractionation and were found to be associated with DNA damage. Gallic acid exhibited the highest antimicrobial activity among the phenolic compounds isolated from the aqueous fraction. The compounds associated to cytotoxicity and antimicrobial activities could be responsible to the effects of this species used in traditional medicine.Key words: Himatanthus sucuuba, iridoids, phenolics, cytotoxicity, antibacterial

Stalked protozoa identification by image analysis and multivariable statistical techniques

Protozoa are considered good indicators of the treatment quality in activated sludge systems as they are sensitive to physical, chemical and operational processes. Therefore, it is possible to correlate the predominance of certain species or groups and several operational parameters of the plant. This work presents a semi-automatic image analysis procedure for the recognition of the stalked protozoa species most frequently found in WWTP by determining the physical, morphological and signature data and subsequent processing by discriminant analysis and neural network techniques. Physical descriptors were found to be responsible the largest identification ability and the crucial Opercularia and V. microstoma micro-organisms identification provided some degree of confidence to establish their presence in WWTP

Development of an image analysis procedure for identifying protozoa and metazoa typical of activated sludge system

A procedure for the semi-automatic identification of the main protozoa and metazoa species present in the activated sludge of wastewater treatment plants was developed. This procedure was based on both image processing and multivariable statistical methodologies, leading to the use of the image analysis morphological descriptors by discriminant analysis and neural network techniques. The image analysis programwritten in Matlab has proved to be adequate in terms of protozoa and metazoa recognition, as well as for the operating conditions assessment.National Council of Scientific and Technological Development of Brazil (CNPq); BIEURAM III ALFA co-operation project (European Commission); Fundação para a Ciência e a Tecnologia (FCT

Recognition of protozoa and metazoa using image analysis tools, discriminant analysis, neural networks and decision trees

Protozoa and metazoa are considered good indicators of the treatment quality in activated sludge systems due to the fact that these organisms are fairly sensitive to physical, chemical and operational processes. Therefore, it is possible to establish close relationships between the predominance of certain species or groups of species and several operational parameters of the plant, such as the biotic indices, namely the Sludge Biotic Index (SBI). This procedure requires the identification, classification and enumeration of the different species, which is usually achieved manually implying both time and expertise availability. Digital image analysis combined with multivariate statistical techniques has proved to be a useful tool to classify and quantify organisms in an automatic and not subjective way. Thiswork presents a semi-automatic image analysis procedure for protozoa and metazoa recognition developed in Matlab language. The obtained morphological descriptors were analyzed using discriminant analysis, neural network and decision trees multivariable statistical techniques to identify and classify each protozoan or metazoan. The obtained procedure was quite adequate for distinguishing between the non-sessile protozoa classes and also for the metazoa classes, with high values for the overall species recognition with the exception of sessile protozoa. In terms of the wastewater conditions assessment the obtained results were found to be suitable for the prediction of these conditions. Finally, the discriminant analysis and neural networks results were found to be quite similar whereas the decision trees technique was less appropriate.National Council of Scientific and Technological Development of Brazil (CNPq); BI-EURAM III ALFA co-operation project (European Commission); Fundação para a Ciência e a Tecnologia (FCT)