Evaluation of the Biological Sampling Kit (BiSKit) for Large-Area Surface Sampling

Current surface sampling methods for microbial contaminants are designed to sample small areas and utilize culture analysis. The total number of microbes recovered is low because a small area is sampled, making detection of a potential pathogen more difficult. Furthermore, sampling of small areas requires a greater number of samples to be collected, which delays the reporting of results, taxes laboratory resources and staffing, and increases analysis costs. A new biological surface sampling method, the Biological Sampling Kit (BiSKit), designed to sample large areas and to be compatible with testing with a variety of technologies, including PCR and immunoassay, was evaluated and compared to other surface sampling strategies. In experimental room trials, wood laminate and metal surfaces were contaminated by aerosolization of Bacillus atrophaeus spores, a simulant for Bacillus anthracis, into the room, followed by settling of the spores onto the test surfaces. The surfaces were sampled with the BiSKit, a cotton-based swab, and a foam-based swab. Samples were analyzed by culturing, quantitative PCR, and immunological assays. The results showed that the large surface area (1 m2) sampled with the BiSKit resulted in concentrations of B. atrophaeus in samples that were up to 10-fold higher than the concentrations obtained with the other methods tested. A comparison of wet and dry sampling with the BiSKit indicated that dry sampling was more efficient (efficiency, 18.4%) than wet sampling (efficiency, 11.3%). The sensitivities of detection of B. atrophaeus on metal surfaces were 42 ± 5.8 CFU/m2 for wet sampling and 100.5 ± 10.2 CFU/m2 for dry sampling. These results demonstrate that the use of a sampling device capable of sampling larger areas results in higher sensitivity than that obtained with currently available methods and has the advantage of sampling larger areas, thus requiring collection of fewer samples per site

Lung cancer mortality in a cohort of workers in a petrochemical plant: occupational or residential risk?

Gela area is an Italian polluted site qualifying for remediation because of widespread contamination from a petrochemical complex. This study investigates mortality and morbidity of the cohort of employees in Gela petrochemical plant with the aim of disentangling the health effect of work and residence. Work experience was classified in terms of job title, while an ad hoc mobility model was applied to define qualitative categories of residence in Gela as probable residents and probable commuters. Mortality rate ratio for lung cancer was 1.60 (90% CI 1.01-2.53) in workers probable resindents compared to probable commuters. For the same comparison, Hospital Discharge Prevalence Ratio for COPD was 1.39 (0.94-2.07). The crude categories of work and residence limits the interpretation of the causal nature of the study results. Despite several limitations, the results for respiratory pathologies are compatible with an etiological role of the documented contamination.The purpose of the present study is to examine the role of environmental (non occupational) exposures in lung cancer risk among petrochemical workers at a large petrochemical plant built on the Sicilian coast in the immediate vicinity of the town of Gela, Italy in 1960. The cohort included workers employed in the Gela petrochemical plant in 1960-1993. We looked at mortality rates for the period 1960-2002. An internal comparison was performed between two categories of workers with different likelihood of residence in Gela during the period of employment. The rate ratio of mortality from lung cancer comparing "probable residents" with "possible non residents," adjusted for age, calendar period, andjob classification (only blue collar, only white collar and both), was 1.66 (90% Confidence Interval 1.07-2.58). Although the information collected is quite sparse and no inferences can be made about risk sources, the results show a possible excess of residential/environmental risk from lung cancer mortality for those workers more likely to have been residents in Gela

Application of Computer Vision for quality control in frozen mixed berries production: colour calibration issues

Computer vision is becoming increasingly important in quality control of many food processes. The appearance properties of food products (colour, texture, shape and size) are, in fact, correlated with organoleptic characteristics and/or the presence of defects. Quality control based on image processing eliminates the subjectivity of human visual inspection, allowing rapid and non-destructive analysis. However, most food matrices show a wide variability in appearance features, therefore robust and customized image elaboration algorithms have to be implemented for each specific product. For this reason, quality control by visual inspection is still rather diffused in several food processes. The case study inspiring this paper concerns the production of frozen mixed berries. Once frozen, different kinds of berries are mixed together, in different amounts, according to a recipe. The correct quantity of each kind of fruit, within a certain tolerance, has to be ensured by producers. Quality control relies on bringing few samples for each production lot (samples of the same weight) and, manually, counting the amount of each species. This operation is tedious, subject to errors, and time consuming, while a computer vision system (CVS) could determine the amount of each kind of berries in a few seconds. This paper discusses the problem of colour calibration of the CVS used for frozen berries mixture evaluation. Images are acquired by a digital camera coupled with a dome lighting system, which gives a homogeneous illumination on the entire visible surface of the berries, and a flat bed scanner. RBG device dependent data are then mapped onto CIELab colorimetric colour space using different transformation operators. The obtained results show that the proposed calibration procedure leads to colour discrepancies comparable or even below the human eyes sensibility

High incidence of classic Kaposi's sarcoma in Mantua, Po Valley, Northern Italy (1989–1998)

The incidence of classic Kaposi's sarcoma was estimated in the province of Mantua, Po Valley, Northern Italy, yielding age-standardized rates of 2.5/100 000 men and 0.7/100 000 women (1989–98). Elevated rates in the rural zone of Viadana/Sabbioneta (5.0/100 000 men and 2.8/100 000 women) are among the highest so far reported for Italian communities. © 2001 Cancer Research Campaign http://www.bjcancer.co

Determination of the Efficacy of Two Building Decontamination Strategies by Surface Sampling with Culture and Quantitative PCR Analysis

The efficacy of currently available decontamination strategies for the treatment of indoor furnishings contaminated with bioterrorism agents is poorly understood. Efficacy testing of decontamination products in a controlled environment is needed to ensure that effective methods are used to decontaminate domestic and workplace settings. An experimental room supplied with materials used in office furnishings (i.e., wood laminate, painted metal, and vinyl tile) was used with controlled dry aerosol releases of endospores of Bacillus atrophaeus (“Bacillus subtilis subsp. niger,” also referred to as BG), a Bacillus anthracis surrogate. Studies were performed using two test products, a foam decontaminant and chlorine dioxide gas. Surface samples were collected pre- and posttreatment with three sampling methods and analyzed by culture and quantitative PCR (QPCR). Additional aerosol releases with environmental background present on the surface materials were also conducted to determine if there was any interference with decontamination or sample analysis. Culture results indicated that 105 to 106 CFU per sample were present on surfaces before decontamination. After decontamination with the foam, no culturable B. atrophaeus spores were detected. After decontamination with chlorine dioxide gas, no culturable B. atrophaeus was detected in 24 of 27 samples (89%). However, QPCR analysis showed that B. atrophaeus DNA was still present after decontamination with both methods. Environmental background material had no apparent effect on decontamination, but inhibition of the QPCR assay was observed. These results demonstrate the effectiveness of two decontamination methods and illustrate the utility of surface sampling and QPCR analysis for the evaluation of decontamination strategies

Cooperative Agricultural Operations of Aerial and Ground Unmanned Vehicles

Precision agriculture comprises a set of technologies that combines sensors, information systems, enhanced machinery, and informed management to optimize production by accounting for variability and uncertainties within agricultural systems. Autonomous ground and aerial vehicle can lead to favorable improvements in management by performing in-field tasks in a time-effective way. Greater benefits can be achieved by allowing cooperation and collaborative action among Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs). A multi-phase approach is here proposed, where each unmanned vehicle involved has been conceived and will be designed to implement innovative solutions for automated navigation and infield operations within a complex irregular and unstructured scenario as vineyards in sloped terrains

Cooperation of unmanned systems for agricultural applications: A theoretical framework

Agriculture 4.0 comprises a set of technologies that combines sensors, information systems, enhanced machinery, and informed management with the objective of optimising production by accounting for variabilities and uncertainties within agricultural systems. Autonomous ground and aerial vehicles can lead to favourable improvements in management by performing in-field tasks in a time-effective way. In particular, greater benefits can be achieved by allowing cooperation and collaborative action among unmanned vehicles, both aerial and ground, to perform in-field operations in precise and time-effective ways. In this work, the preliminary and crucial step of analysing and understanding the technical and methodological challenges concerning the main problems involved is performed. An overview of the agricultural scenarios that can benefit from using collaborative machines and the corresponding cooperative schemes typically adopted in this framework are presented. A collection of kinematic and dynamic models for different categories of autonomous aerial and ground vehicles is provided, which represents a crucial step in understanding the vehicles behaviour when full autonomy is desired. Last, a collection of the state-of-the-art technologies for the autonomous guidance of drones is provided, summarising their peculiar characteristics, and highlighting their advantages and shortcomings with a specific focus on the Agriculture 4.0 framework. A companion paper reports the application of some of these techniques in a complete case study in sloped vineyards, applying the proposed multi-phase collaborative scheme introduced here