997 resultados para drug manufacturing
Resumo:
Fiber meshes of poly(hydroxybutyrate) (PHB) and poly(hydroxybutyrate)/ poly(ethylene oxide) (PHB/PEO) with different concentrations of chlorhexidine (CHX) were prepared by electrospinning, for assessment as a polymer based drug delivery system. The electrospun fibers were characterized at morphological, molecular and mechanical levels. The bactericidal potential of PHB and PHB/PEO electrospun fibers with and without CHX was investigated against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) by disk diffusion susceptibility tests. Electrospun fibers containing CHX exhibited bactericidal activity. PHB/PEO-1%CHX displayed higher CHX release levels and equivalent antibacterial activity when compared to PHB/PEO with 5 and 10 wt% CHX. Bactericidal performance of samples with 1 wt% CHX was assessed by Colony Forming Units (CFU), where a reduction of 100 % and 99.69 % against E. coli and S. aureus were achieved, respectively.
Resumo:
The real Cloud and Ubiquitous Manufacturing systems require effectiveness and permanent availability of resources, their capacity and scalability. One of the most important problems for applications management over cloud based platforms, which are expected to support efficient scalability and resources coordination following SaaS implementation model, is their interoperability. Even application dashboards need to easily incorporate those new applications, their interoperability still remains a big problem to override. So, the possibility to expand these dashboards with efficiently integrated communicational cloud based services (cloudlets) represents a relevant added value as well as contributes to solving the interoperability problem. Following the architecture for integration of enriched existing cloud services, as instances of manufacturing resources, this paper: a) proposes a cloud based web platform to support dashboard integrating communicational services, and b) describe an experimentation to sustain the theory that the effective and efficient interoperability, especially in dynamic environments, could be achieved only with human intervention.
Resumo:
We present a novel data analysis strategy which combined with subcellular fractionation and liquid chromatography-mass spectrometry (LC-MS) based proteomics provides a simple and effective workflow for global drug profiling. Five subcellular fractions were obtained by differential centrifugation followed by high resolution LC-MS and complete functional regulation analysis. The methodology combines functional regulation and enrichment analysis into a single visual summary. The workflow enables improved insight into perturbations caused by drugs. We provide a statistical argument to demonstrate that even crude subcellular fractions leads to improved functional characterization. We demonstrate this data analysis strategy on data obtained in a MS-based global drug profiling study. However, this strategy can also be performed on other types of large scale biological data.
Resumo:
Epidemiological studies of drug misusers have until recently relied on two main forms of sampling: probability and convenience. The former has been used when the aim was simply to estimate the prevalence of the condition and the latter when in depth studies of the characteristics, profiles and behaviour of drug users were required, but each method has its limitations. Probability samples become impracticable when the prevalence of the condition is very low, less than 0.5% for example, or when the condition being studied is a clandestine activity such as illicit drug use. When stratified random samples are used, it may be difficult to obtain a truly representative sample, depending on the quality of the information used to develop the stratification strategy. The main limitation of studies using convenience samples is that the results cannot be generalised to the whole population of drug users due to selection bias and a lack of information concerning the sampling frame. New methods have been developed which aim to overcome some of these difficulties, for example, social network analysis, snowball sampling, capture-recapture techniques, privileged access interviewer method and contact tracing. All these methods have been applied to the study of drug misuse. The various methods are described and examples of their use given, drawn from both the Brazilian and international drug misuse literature.
Resumo:
OBJECTIVE: To assess the frequency of combination of antidepressants with other drugs and risk of drug interactions in the setting public hospital units in Brazil. METHODS: Prescriptions of all patients admitted to a public hospital from November 1996 to February 1997 were surveyed from the hospital's data processing center in São Paulo, Brazil. A manual search of case notes of all patients admitted to the psychiatric unit from January 1993 to December 1995 and all patients registered in the affective disorders outpatient clinic in December 1996 was carried out. Patients taking any antidepressant were identified and concomitant use of drugs was checked. By means of a software program (Micromedex®) drug interactions were identified. RESULTS: Out of 6,844 patients admitted to the hospital, 63 (0.9%) used antidepressants and 16 (25.3%) were at risk of drug interaction. Out of 311 patients in the psychiatric unit, 63 (20.2%) used antidepressants and 13 of them (20.6%) were at risk. Out of 87 patients in the affective disorders outpatient clinic, 43 (49.4%) took antidepressants and 7 (16.2%) were at risk. In general, the use of antidepressants was recorded in 169 patients and 36 (21.3%) were at risk of drug interactions. Twenty different forms of combinations at risk of drug interactions were identified: four were classified as mild, 15 moderate and one severe interaction. CONCLUSION: In the hospital general units the number of drug interactions per patient was higher than in the psychiatric unit; and prescription for depression was lower than expected.
Resumo:
A novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS), Case-based Reasoning (CBR), and Bio-Inspired Optimization Techniques (BIT) will be described. AC has emerged as a paradigm aiming at incorporating applications with a management structure similar to the central nervous system. The main intentions are to improve resource utilization and service quality. In this paper we envisage the use of MAS paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with AC properties, in order to reduce the complexity of managing manufacturing systems and human interference. The proposed CBR based Intelligent Scheduling System was evaluated under different dynamic manufacturing scenarios.
Resumo:
Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).
Resumo:
This chapter addresses the resolution of scheduling in manufacturing systems subject to perturbations. The planning of Manufacturing Systems involves frequently the resolution of a huge amount and variety of combinatorial optimisation problems with an important impact on the performance of manufacturing organisations. Examples of those problems are the sequencing and scheduling problems in manufacturing management, routing and transportation, layout design and timetabling problems.
Resumo:
OBJECTIVE: Many business organizations in Brazil have adopted drug testing programs in the workplace since 1992. Rehabilitation, rather than layoff and disciplinary measures, has been offered as part of the Brazilian employee assistance programs. The purpose study is to profile drug abuse among company workers of different Brazilian geographical regions. METHODS: Urine samples of 12,700 workers from five geographical regions were tested for the most common illicit drugs of abuse in the country: marijuana, cocaine, and amphetamine. Enzyme multiplied immunoassay technique (EMIT) and gas chromatography coupled with mass spectrometry (GC/MS) were the techniques utilized for urine testing. The distribution of collected urine samples according to geographical regions was: 72.0% southeast, 13.8% northeast, 7.9% south, 5.7% central west and 0.6% north. RESULTS: Of all samples analyzed, 1.8% was found to be positive for drugs: 0.5% from the south region, 1.1% from northeast, 1.2% from central west, 1.3% from north, and 2.2% from southeast. Of these, 59.9% was marijuana, 17.7% cocaine, 14.6% amphetamine, and 7.7% associated drugs. CONCLUSIONS: The distribution of drugs found in the samples shows a regional variation. Marijuana, however, was found in all regions. Cocaine was seen only in central west and southeast regions. Amphetamine was found in northeast, central west, and southeast regions.
Resumo:
Agility refers to the manufacturing system ability to rapidly adapt to market and environmental changes in efficient and cost-effective ways. This paper addresses the development of self-organization methods to enhance the operations of a scheduling system, by integrating scheduling system, configuration and optimization into a single autonomic process requiring minimal manual intervention to increase productivity and effectiveness while minimizing complexity for users. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to build future Decision Support Systems (DSS) for Scheduling in agile manufacturing environments.
Resumo:
Nowadays, the phenomenon of population ageing represents an worldwide problem, which assumes particular significance in Portugal. As they get older, individuals present more comorbidities and consequently consume an increasing number of drugs, which contributes to a growing drug therapy complexity. The institutionalized elders are particularly affected by this occurrence. Drug therapy complexity is defined as the conciliator of several characteristics of the pharmacotherapy and can affect patient’s safety and medication adherence. It can be measured with Medication Regimen Complexity Index (MRCI). This study aims to determine the drug therapy complexity of institutionalized elders in order to assess the need of pharmacotherapeutic follow-up.