C. difficile surveillance quarterly report: January - March 2012

This quarterly report provides epidemiological data on C. difficile in Northern Ireland, and includes key points, a comprehensive�overview of all C. diff infections, rates, trends, age-specific information�and statistical process control charts. The report also provides information on surveillance methods and data for each hospital and Health and Social Care Trust in Northern Ireland.

S.aureus bacteraemia surveillance quarterly report: January - March 2012

This quarterly report provides epidemiological data on�S. aureus�in Northern Ireland, including overall infection�figures as well as those specific to MRSA and MSSA. The report highlights key points, rates, trends and statistical process control charts. The report also provides information on surveillance methods and data for each hospital and Health and Social Care Trust in Northern Ireland

C. difficile surveillance quarterly report: October - December 2012

This quarterly report provides epidemiological data on C. difficile in Northern Ireland, and includes key points, a comprehensive�overview of all C. diff infections, rates, trends, age-specific information�and statistical process control charts. The report also provides information on surveillance methods and data for each hospital and Health and Social Care Trust in Northern Ireland.

S.aureus bacteraemia surveillance quarterly report: October - December 2012

This quarterly report provides epidemiological data on�S. aureus�in Northern Ireland, including overall infection�figures as well as those specific to MRSA and MSSA. The report highlights key points, rates, trends and statistical process control charts. The report also provides information on surveillance methods and data for each hospital and Health and Social Care Trust in Northern Ireland

S. aureus bacteraemia surveillance quarterly report: October-December 2010

This quarterly report provides epidemiological data on�S. aureus�in Northern Ireland, including overall infection�figures as well as those specific to MRSA and MSSA. The report highlights key points, rates, trends and statistical process control charts. The report also provides information on surveillance methods and data for each hospital and Health and Social Care Trust in Northern Ireland.

C. difficile surveillance quarterly report: October-December 2010

This quarterly report provides epidemiological data on C. difficile in Northern Ireland, and includes key points, a comprehensive�overview of all C. diff infections, rates, trends, age-specific information�and statistical process control charts. The report also provides information on surveillance methods and data for each hospital and Health and Social Care Trust in Northern Ireland.

C. difficile and S.aureus bacteraemia surveillance quarterly reports

Quarterly reports provide epidemiological data on�C. difficile and S. aureus�in Northern Ireland. The report highlights key points, rates, trends and statistical process control charts. The report also provides information on surveillance methods and data for each hospital and Health and Social Care Trust in Northern Ireland.Click here to see the latest reports

C. difficle surveillance quarterly report: July-September 2015

This quarterly report provides epidemiological data on�C. difficile�in Northern Ireland, and includes key points, a comprehensive�overview of all�C. diff�infections, rates, trends, age-specific information�and statistical process control charts.

"The 3/3 strategy": a successful multifaceted hospital wide hand hygiene intervention based on WHO and continuous quality improvement methodology.

BACKGROUND Only multifaceted hospital wide interventions have been successful in achieving sustained improvements in hand hygiene (HH) compliance. METHODOLOGY/PRINCIPAL FINDINGS Pre-post intervention study of HH performance at baseline (October 2007-December 2009) and during intervention, which included two phases. Phase 1 (2010) included multimodal WHO approach. Phase 2 (2011) added Continuous Quality Improvement (CQI) tools and was based on: a) Increase of alcohol hand rub (AHR) solution placement (from 0.57 dispensers/bed to 1.56); b) Increase in frequency of audits (three days every three weeks: "3/3 strategy"); c) Implementation of a standardized register form of HH corrective actions; d) Statistical Process Control (SPC) as time series analysis methodology through appropriate control charts. During the intervention period we performed 819 scheduled direct observation audits which provided data from 11,714 HH opportunities. The most remarkable findings were: a) significant improvements in HH compliance with respect to baseline (25% mean increase); b) sustained high level (82%) of HH compliance during intervention; c) significant increase in AHRs consumption over time; c) significant decrease in the rate of healthcare-acquired MRSA; d) small but significant improvements in HH compliance when comparing phase 2 to phase 1 [79.5% (95% CI: 78.2-80.7) vs 84.6% (95% CI:83.8-85.4), p<0.05]; e) successful use of control charts to identify significant negative and positive deviations (special causes) related to the HH compliance process over time ("positive": 90.1% as highest HH compliance coinciding with the "World hygiene day"; and "negative":73.7% as lowest HH compliance coinciding with a statutory lay-off proceeding). CONCLUSIONS/SIGNIFICANCE CQI tools may be a key addition to WHO strategy to maintain a good HH performance over time. In addition, SPC has shown to be a powerful methodology to detect special causes in HH performance (positive and negative) and to help establishing adequate feedback to healthcare workers.

An Experimental Validation of a Statistical-Based Damage Detection Approach, January 2011

In this work, a previously-developed, statistical-based, damage-detection approach was validated for its ability to autonomously detect damage in bridges. The damage-detection approach uses statistical differences in the actual and predicted behavior of the bridge caused under a subset of ambient trucks. The predicted behavior is derived from a statistics-based model trained with field data from the undamaged bridge (not a finite element model). The differences between actual and predicted responses, called residuals, are then used to construct control charts, which compare undamaged and damaged structure data. Validation of the damage-detection approach was achieved by using sacrificial specimens that were mounted to the bridge and exposed to ambient traffic loads and which simulated actual damage-sensitive locations. Different damage types and levels were introduced to the sacrificial specimens to study the sensitivity and applicability. The damage-detection algorithm was able to identify damage, but it also had a high false-positive rate. An evaluation of the sub-components of the damage-detection methodology and methods was completed for the purpose of improving the approach. Several of the underlying assumptions within the algorithm were being violated, which was the source of the false-positives. Furthermore, the lack of an automatic evaluation process was thought to potentially be an impediment to widespread use. Recommendations for the improvement of the methodology were developed and preliminarily evaluated. These recommendations are believed to improve the efficacy of the damage-detection approach.

Kinetic behavior of nitrification in the post-treatment of poultry wastewater in a sequential batch reactor

A sequential batch reactor with suspended biomass and useful volume of 5 L was used in the removal of nutrients and organic matter in workbench scale under optimal conditions obtained by central composite rotational design (CCRD), with cycle time (CT) of 16 h (10.15 h, aerobic phase, and 4.35 h, anoxic phase) and carbon: nitrogen ratio (COD/NO2--N+NO3--N) equal to 6. Complete cycles (20), nitrification followed by denitrification, were evaluated to investigate the kinetic behavior of degradation of organic (COD) and nitrogenated (NH4+-N, NO2--N and NO3--N) matter present in the effluent from a bird slaughterhouse and industrial processing facility, as well as to evaluate the stability of the reactor using Shewhart control charts of individual measures. The results indicate means total inorganic nitrogen (NH4+-N+NO2- -N+NO3--N) removal of 84.32±1.59% and organic matter (COD) of 53.65±8.48% in the complete process (nitrification-denitrification) with the process under statistical control. The nitrifying activity during the aerobic phase estimated from the determination of the kinetic parameters had mean K1 and K2 values of 0.00381±0.00043 min-1 and 0.00381±0.00043 min-1, respectively. The evaluation of the kinetic behavior of the conversion of nitrogen indicated a possible reduction of CT in the anoxic phase, since removals of NO2--N and NO3--N higher than 90% were obtained with only 1 h of denitrification.

Influence of the sample area in the variability of losses in the mechanical harvesting of soybeans

The mechanical harvesting is an important stage in the production process of soybeans and, in this process; the loss of a significant number of grains is common. Despite the existence of mechanisms to monitor these losses, it is still essential to use sampling methods to quantify them. Assuming that the size of the sample area affects the reliability and variability between samples in quantifying losses, this paper aimed to analyze the variability and feasibility of using different sizes of sample area (1, 2 and 3 m²) in quantifying losses in the mechanical harvesting of soybeans. Were sampled 36 sites and the cutting losses, losses by other mechanisms of the combine and total losses were evaluated, as well as the water content in seeds, straw distribution and crop productivity. Data were subjected to statistical analysis (descriptive statistics and analysis of variance) and Statistical Control Process (SCP). The coefficients of variation were similar for the three frames available. Combine losses showed stable behavior, whereas cutting losses and total losses showed unstable behavior. The frame size did not affect the quantification and variability of losses in the mechanical harvesting of soybeans, thus a frame of 1 m² can be used for determining losses.

Perdas de grãos e distribuição de palha na colheita mecanizada de soja

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

Caracterização de água produzida na indústria de petróleo para fins de descarte e otimização do processo de separação óleo/água

The oil industry has several segments that can impact the environment. Among these, produced water which has been highlight in the environmental problem because of the great volume generated and its toxic composition. Those waters are the major source of waste in the oil industry. The composition of the produced water is strongly dependent on the production field. A good example is the wastewater produced on a Petrobras operating unit of Rio Grande do Norte and Ceará (UO-RNCE). A single effluent treatment station (ETS) of this unit receives effluent from 48 wells (onshore and offshore), which leads a large fluctuations in the water quality that can become a complicating factor for future treatment processes. The present work aims to realize a diagnosis of a sample of produced water from the OU - RNCE in compliance to certain physical and physico-chemical parameters (chloride concentration, conductivity, dissolved oxygen, pH, TOG (oil & grease), nitrate concentration, turbidity, salinity and temperature). The analysis of the effluent is accomplished by means of a MP TROLL 9500 Multiparameter probe, a TOG/TPH Infracal from Wilks Enterprise Corp. - Model HATR - T (TOG) and a MD-31 condutivimeter of Digimed. Results were analyzed by univariated and multivariated analysis (principal component analysis) associated statistical control charts. The multivariate analysis showed a negative correlation between dissolved oxygen and turbidity (-0.55) and positive correlations between salinity and chloride (1), conductivity, chloride and salinity (0.70). Multivariated analysis showed there are seven principal components which can explain the variability of the parameters. The variables, salinity, conductivity and chloride were the most important variables, with, higher sampling variance. Statistical control charts have helped to establish a general trend between the physical and chemical evaluated parameters

A new chart based on sample variances for monitoring the covariance matrix of multivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)