Contamination Grade Research Articles

Lead (Pb) Pollution in Soil: A Systematic Review and Meta-Analysis of Contamination Grade and Health Risk in Mexico

Lead (Pb) is a toxic metal associated with several health disorders. The mining and Pb battery industry are related to Pb increase in air, water, and soil. Mexico is an important worldwide Pb producer; however, reviews on environmental Pb contamination in Mexico are insufficient. Since Pb remains stable in soil and its concentration is an indicator of Pb exposure, this systematic review focused on reports of Pb concentrations in soil from Mexico published in 2010–2023. The retrieved reports were ordered, and contamination grade and health risk were estimated for location. From 36 retrieved reports, 24 were associated with mining Pb pollution, while a unique report mentioned the battery industry. The publications evaluated mining (13), agricultural (11), and residential (16) soils. Pb concentrations in soil were higher than the allowed limits in more than half of the reports. According to the Pb concentrations in soil, the locations evaluated in Mexico presented a contamination grade from heavily contaminated to extremely contaminated and health risks results suggested severe hazards, particularly for children. This work can guide other researchers to identify potentially contaminated but understudied Mexican locations.

Urban geochemistry of heavy metals in road dust from Cairo megacity, Egypt: enrichment, sources, contamination, and health risks

Traffic emissions, overpopulation, and poor urban planning have degraded the environmental quality of the Greater Cairo megacity. As road dust is considered the main sink of pollutants in urban environments, thirty road dust samples from six major roads were collected. ICP-OES was used to analyze the samples in order to determine the contamination grade using the pollution indices, decipher metal sources and geochemical associations using multivariate analysis, and evaluate the ecological and human health risks. The average contents of heavy metals were arranged in decreasing order: Fe (1181.12), Zn (201.36), Pb (66.10), Ni (32.42), Cu (26.07), Cr (26.00), Co (14.78), As (2.76), and Hg (0.93) mg/kg. The spatial pattern showed that new urban communities exhibited lower contamination levels compared to unplanned old districts, especially for traffic elements (Pb, Zn, and Cu). The highest Igeo mean value was observed for Hg (3.34) followed by Zn (1.34), Pb (1.24), Ni (0.10), As (− 0.19), Co (− 0.24), Cu (− 0.73), and Cr (− 1.05). Additionally, CF values indicated very high contamination levels for Pb and Zn, whereas the highest PLI value was observed at Ramses Street. All EF values were higher than 1.5, indicating the anthropogenic enrichment of metals. RI values classified Cairo as a region with considerable ecological risk, observing that Hg was the main contributor. Correlation analysis and PCA showed that Pb and Zn originated from vehicle exhaust, Hg, Cu, and As from domestic and industrial activities, and Fe and Co from natural origin. Cr and Ni exhibited potential carcinogenic risks for children through ingestion; conversely, the non-carcinogenic risks were within safe levels. As a result, the use of clean energy is recommended to mitigate the accumulation of heavy metals in road dust and to improve the quality of life.

Enrichment, sources, and distributions of toxic elements in the farming land's topsoil near a heavily industrialized area of central Bangladesh, and associated risks assessment

Toxic element accumulation in the surrounding soils of the advanced industry- and agriculture-oriented areas may lead to severe environmental degradation and harmful impact on inhabitants. This work examined the concentration of some concerned toxic elements (Cr, Pb, Cd, Cu, As, and Ni) in the representative topsoil from 10 industrially contaminated sites in central Bangladesh (Narayanganj district) using an Inductively Coupled Plasma Mass Spectrometer concerning the probable ecological and human health risks. The mean concentrations (mg/kg) of the elements were found in the order of Ni (58.1 ± 11.8) > Pb (34.1 ± 14.3) > Cr (32.1 ± 6.77) > Cu (14.5 ± 3.30) > Cd (2.74 ± 1.08) > As (1.49 ± 0.43). The findings pointed out that diversified manmade events enhanced the intensities of elemental contamination through the studied sites. Source analysis showed that Cr, Pb, As, and Cd may originate from industrial wastewater and agricultural activities, whereas Cu and Ni came from natural sources. The geo-accumulation index level for Cd (1.70–3.39) was determined as grade 3 (moderately to strongly polluted), the enrichment factor score for Cd (13.9) fell in the very severe enhanced category (cluster 5), and the highest contamination factor value was found for Cd (15.7). The contamination degree values for all the tested elements signify a moderate to severe contamination grade; conversely, pollution load index levels depicted the nonexistence of elemental pollution. The assessment revealed serious Cd pollution in agricultural soils and moderate to significant potential ecological risk for the rest of the examined toxic elements. Furthermore, hazard index values exceeded the safe exposure levels, indicating that there was potential non-carcinogenic risk in the soils for children and adults. Ingestion exposure had much higher carcinogenic risk values than inhalation and cutaneous exposure, and children are exposed to considerable carcinogenic hazards. Therefore, it is suggested that the harmful practices that expose this farming soil to contaminants should be stopped immediately and effective environment-friendly techniques of waste management and effluent treatment should be employed in the study area.

Pixel-Level Assessment Model of Contamination Conditions of Composite Insulators Based on Hyperspectral Imaging Technology and a Semi-Supervised Ladder Network

Real-time and accurate supervision of contamination conditions of composite insulators can effectively prevent the occurrence of pollution flashover accidents and ensure stable operation of the power system. In this article, a refined and controllable artificial contamination experiment is carried out, in which a total of 60 types of pollutants (12 contamination conditions) are formed by combining 20 types of equivalent salt deposit densities (ESDDs) at four contamination levels and three types nonsoluble deposit densities (NSDDs)/ESDD ratios to pollute composite insulators. Hyperspectral imaging technology is also introduced to extract the spectral data of polluted insulators, and the changing pattern of spectral curves under different pollution conditions is studied. Then, the spectral curve is preprocessed by black-and-white correction, standard normal variate (SNV), and detrending correction, and the preprocessed data are analyzed for band correlation. According to the variation pattern of the spectral curve and the band correlation characteristics, the full set of bands is divided into red, other visible, and near-infrared regions for principal component transformation respectively. Compared with the traditional principal component transformation, the former can reduce the calculation amount by 66%. Finally, to solve the problem of insufficiently labeled samples in practical engineering, a semi-supervised ladder network is used to realize pixel-level evaluation of insulator contamination conditions, and evaluation results are visualized. Research results show the pixel-level evaluation method can accurately evaluate contamination conditions of different areas on the surface of composite insulators. A semi-supervised model can guarantee the accuracy of classification results when there are few labeled samples. When the supervision rate is 10%, the classification accuracy of a semi-supervised model for contamination grade, NSDD/ESDD ratio, and contamination condition is higher than 95%, while that of a supervised model is lower than 90%.

Correlative microscopy approach for micro- and nanoplastics detection in plant matrix

The world-wide plastics pollution into nature enters the human food chain as degradation products, influencing environmental habitat and health. Micro- and nanoplastics as foreign bodies contaminating beverages and foods on the cellular level are likely to have a long-term impact on nutrition growth, public and personal health. Nanoparticles and their spatial location are generally difficult to detect in biological specimens, especially plastic particles due to their analogous hydrocarbon-based matrix. Reliable analysis methods for the discovery of micro- and nanoplastic particles in entities are not fully established yet. We are therefore developing a correlative workflow for detecting plastics residuals in cellular tissue. We determined that light microscopy (LM) is usable for a coarse estimation of the contamination grade of plant samples. Due to its optical diffraction limit, LM rather detects nanoparticle patches than single particles, shown with fluorescent particles. Scanning electron microscopy (SEM) instead provides higher resolution, especially for single particle detection. EM sample staining is still required to depict polymerous nanoparticle specimens. Using LM and SEM data in a CLEM approach with TESCAN CORAL, discovery of contaminated plant areas is possible with single nanoparticle resolution. It reveals that nanoparticles seem to be tightly attached to the plant material. It indicates further that basic food cleaning procedures might be insufficient for particle removal. The workflow circumvents correlative sample 3D-topography issues. But insights into the plant matrix is best possible with z-information. Therefore, we additionally use focused ion beam (FIB) to determine inclusions of micro- and nanoplastics in the tissue/cellular matrix, investigating the optimal procedural approach as model for biomaterial systems. Procedural correlative microscopy provides a promising analysis method for the semiquantitative analysis of micro- and nanoparticles plant contaminations.

Study the Contamination Level of Organochlorine Pesticides in Fruits During Summer Season

Fruits have nutritional value, but they can also be sources of toxic contaminants, such as pesticide residues. Pesticides used for fruit production results in increased health risks and health costs, humiliation of the environment and productivity loss. This research aimed to conduct to estimate presence of pesticide residues in summer season fruit purchase from local market. Pesticides were precisely detected in fruit samples collected from the market and the technique (GC-ECD) was used for analyzing and studying organochlorine pesticides in three fruits of the summer season, i.e., (plum, kiwi fruit and pineapple). The maximum residual limits (MRLs) values were compared with pesticide concentrations. In fruit sample, mean values of pesticide concentration residues were found. All fruits were found to be contaminated with pesticides. The concentrations of monitoring pesticides were less than the (MRL) values. However, the severe health problems may be created by the regular eating of pesticide infected fruits. It can be concluded that the periodical monitoring of fruits for pesticide residues is essential to evaluating their contamination grade and producing awareness on the health hazards involved in pesticide misuse.

New sensitive ambient mass spectrometric method combined with chemometric modelling for the analysis of Equisetum palustre L. contaminations in the traditional herb Equiseti herba

The aim of this study was to develop a new and sensitive ambient mass spectrometric method in combination with multivariate data analysis to classify and quantify contaminations of the traditional herb Equiseti herba through the similar looking E. palustre. Due to its morphological similarity and the often-overlapping habitats, mix-ups of the two plants are common. This is concerning since E. palustre contains substances that are potentially toxic to humans, such as the piperidine alkaloids palustrine and palustridiene. Next to macroscopic and microscopic examination, the identification of Equiseti herba in the European Pharmacopoeia is carried out by means of thin layer chromatography, which must detect up to 5% of foreign compounds. The results of the chemometric models were built from the mass spectrometric data. Furthermore, they were compared with a near infrared spectroscopy method combined with multivariate data analysis, since this type of spectroscopy has already been established in quality control. As a result, the linear discriminant model obtained from the mass spectrometric data could classify an independent set of artificial contaminations of E. arvense through E. palustre with high correctness as low as 1% dry weight contamination grade. In addition, quantification through a partial least square model showed adequate results for a location of the grade of contamination. In conclusion, the new ambient mass spectrometric method presents itself superior to the respective near infrared method and the chemometric models built from its data as well as the official thin layer chromatography of the European Pharmacopoeia.

The injury characteristics of open pilon fractures predictive of complications

ObjectiveDetermine predictive injury factors for wound complications in open pilon fractures (OTA/AO 43B and 43C). DesignRetrospective Case Series. SettingLevel I Trauma Center. Patients/participantsA total of 61 open pilon fractures in 60 patients were evaluated after meeting inclusion and exclusion criteria. InterventionThe majority of injuries underwent a staged protocol with immediate antibiotics, debridement, irrigation and external fixation. Following soft tissue stabilization, internal fixation was performed and wound closure achieved in a coordinated fashion depending on the type of closure required. Main outcome measurementsEarly amputation rate, 90-day major (wound dehiscence or deep infection requiring operative intervention) and minor (superficial infection) wound complications. ResultsFour patients incurred early amputations, 11 had major wound complications and 5 had minor wound complications. An early amputation was more likely if they presented with an OTA Open Fracture Classification (OTA-OFC) Bone Loss Grade 3. A major wound complication was more likely if they presented with a fall from > 3 m, a multifragmentary articular surface, a segmental fibula fracture, or an OTA-OFC Contamination Grade 3. A multifragmentary articular surface was also predictive of developing any wound complication. ConclusionsOpen pilon fractures are severe, limb-threatening injuries and are at risk for wound complications. Patients presenting with these injuries and a predictive factor should be counseled regarding the possibility of early limb loss or experiencing a wound complication that will require additional treatment. Level of evidenceLevel III

Insulator Contamination Grade Recognition Using the Deep Learning of Color Information of Images

To implement the non-contact detection of contamination on insulators, a contamination severity assessment methodology using the deep learning of the colored image information of insulators can be used. For the insulator images taken at the substation site, a mathematical morphology-improved optimal entropic threshold (OET) method is utilized to extract the insulator from the background. By performing feature calculations of insulator images in RGB and HSI color spaces, sixty-six color features are obtained. By fusing the features of the two color spaces using kernel principal component analysis (KPCA), fused features are obtained. The recognition of contamination grades is then accomplished with a deep belief network (DBN) that consists of a three-layered restricted Boltzmann machine. The experimental results of the images taken on-site show that the fused features obtained by the KPCA can fully reflect the contamination state of the insulators. Compared with the identification obtained using RGB or HSI color-space features alone, accuracy is significantly improved, and insulator contamination grades can be effectively identified. The research provides a new method for the accurate, efficient, and non-contact detection of insulator contamination grades.

Pollution and Irrigation Applicability of Surface Water from Wet, Normal, and Dry Periods in the Huixian Karst Wetland, China

To reveal the hydrochemical characteristics of karst wetland located in a subtropical area and at lower elevations in China, 27 surface water samples were collected during three periods (wet, normal, and dry) in the Huixian karst wetland to investigate the distributions, pollution, and irrigation application of 12 inorganic ions and 10 heavy metals. Based on their concentrations, the Nemerow index and the four evaluation systems of the sodium adsorption ratio (SAR), sodium concentration (SC), permeability index (PI), and residual sodium carbonate (RSC) were applied to evaluate the pollution characteristics and irrigation application. It was found that the water type in this area was Ca2+-HCO3- and weakly alkaline. Regarding the 12 inorganic ions and 10 heavy metals, NH4+ exceeded the Chinese standards for drinking water with an exceedance rate of 25.93%, and the exceedance rates of Al, Mn, and Hg were 11.11%, 44.44%, and 37.04%, respectively. The spatiotemporal scaling effect on inorganic ions was lower than that of heavy metals, and the distributions of the inorganic ions and heavy metals were in the order of wet period > normal period > dry period. However, the surface water quality in the Huixian karst wetland was generally well-protected based on the pollution assessment. The Nemerow index ranged from 0.75 to 2.69, which recognized the main pollution contributors as NH4+, Mn, Al, and Hg with the contamination grade from slight pollution to moderate pollution, especially in the core area during the wet period. According to the limits of standards for irrigation water quality and environmental quality for surface water, as well as the evaluation results of the SAR, SC, PI, and RSC, the surface water in the Huixian karst wetland was generally suitable for irrigation, and the water quality in the dry period was better than that in the wet and normal periods. The surface water from site PH1 during the normal period with 19.1 μg·L-1 of Hg and site FH8 during the wet period with 13.7 mg·L-1 of NH4+ were not suitable for agricultural irrigation.

Intelligent Recognition of Insulator Contamination Grade Based on the Deep Learning of Ultraviolet Discharge Image Information

In order to achieve the noncontact detection of the contamination grade of insulators and to provide guidance for preventing the contamination flashover of insulators based on the pollution state, we propose a contamination grade recognition method based on the deep learning of ultraviolet discharge images using a sparse autoencoder (SAE) and a deep belief network (DBN). Under different humidity conditions, we filmed and preprocessed the ultraviolet discharge images of insulators at different contamination grades and we obtained the ultraviolet spot area sequence as original data for contamination grade recognition. A double-layer sparse autoencoder was used to extract sparse features that could characterize different contamination grades from the ultraviolet spot area sequence. Using the extracted features, a DBN composed of three layers of restricted Boltzmann machine was trained to provide contamination grade recognition. To verify the effectiveness of the method proposed in this paper, high-voltage experiments were performed on contaminated insulators at relative humidity levels of 80%, 85%, and 90%, and ultraviolet images were recorded. The proposed SAE–DBN method was used to identify the ultraviolet images of the insulators with different contamination grades. The recognition accuracy rates at the three humidity levels were 91.25%, 93.125%, and 92.5%. The experimental results showed that this method could accurately recognize the contamination grade of the insulator and provide guidance for the prevention of contamination flashover based on the pollution severity.

Use of polyvinylidene fluoride (PVDF) meshes for ventral hernia repair in emergency surgery.

The implantation of non-absorbable meshes is the gold standard technique for ventral hernia (VH) repairs. However, emergency surgeries are often related to contaminated/infected fields, where the implantation of prosthetic materials may not be recommendable. Our aim was to evaluate the results of polyvinylidene fluoride (PVDF) meshes used for contaminated and/or complicated VH repairs in the acute setting. We conducted a retrospective analysis of patients with VH who underwent emergency surgery involving PVDF meshes, in a tertiary hospital (from November 2013 to September 2019). We analyzed postoperative complications and 1-year recurrence rates. We evaluated the relationships between contamination grade, mesh placement, infectious complications, and recurrences. We gathered data on 123 patients; their mean age was 62.3years, their mean BMI was 31.1kg/m2, and their mean CeDAR index was 51.6. 96.4% of patients had a grade 2-3 ventral hernia according to the Rosen index. The mean defect width was 8cm (IQR 2-18). 93 cases (75.6%) were described as contaminated or dirty surgeries. A PVDF mesh was placed using an IPOM technique in 56.3% of cases, and via interposition location in 39.9%. The one-month recurrence rate was 5.7% and recurrence after one year was 19.1%. The overall mortality rate was 27.6%. Risk of recurrence was related to patients with a Rosen score over 2 (p < 0.001), as well as with postoperative SSI (p = 0.045). Higher recurrence rates were not related to PVDF mesh placement. The use of PVDF meshes for emergency VH repairs in contaminated surgeries seems safe and useful, with reasonable recurrence rates, and acceptable infectious complication rates, similar to those published in the literature.

The rheological properties of masticated natural rubbers and their linear viscoelastic predictions

Premastication of natural rubber (NR) is a common process to ease the incorporation of fillers and chemicals. This research studied the changes in molecular structure, molecular weight (MW), and linear viscoelastic (LVE) properties of the standard Thai NR block grade STR5L, which is the low contamination grade, after mastication for 20 min at 40, 70, and 100 rpm, respectively. The MWs of unmasticated and masticated NRs were quantified by size exclusion chromatography. The “dual constraint” model, which is known to provide good predictions of the LVE properties from the MW and molecular weight distribution (MWD) of linear polymers, was used to correlate the MWs of NRs to their LVE properties. It was found that the dual constraint model could predict the dynamic moduli of NRs masticated at high speeds (70 and 100 rpm), indicating that the rheological behavior of the masticated NRs at 70 and 100 rpm conformed to linear polymers. On the other hand, the predictions for the unmasticated NR and the NR masticated at a lower speed of 40 rpm (NR40 rpm) deviated from the experimental values, especially in the terminal zone. This deviation might be due to the presence of physical gel and microgel in NR, which might still exist at mastication temperatures below 100 °C.

Spectral BRDF measurements of metallic samples for laser processing applications

The spectral bidirectional reflectance distribution function (BRDF) of metals plays an important role in industrial processing involving laser-surface interaction. In particular, in laser metal machining, absorbance is strongly dependent on the radiation incidence angle as well as on finishing and contamination grade of the surface, and in turn it can considerably affect processing results. Very recently, laser radiation is also used to structure metallic surfaces, in order to produce many particular optical effects, ranging from a high level polishing to angular color shifting. Of course, full knowledge of the spectral BRDF of these structured layers makes it possible to infer reflectance or color for any irradiation and viewing angles. In this paper, we present Vis-NIR spectral BRDF measurements of laser-polished metallic, opaque, flat samples commonly employed in such applications. The resulting optical properties seem to be dependent on the atmospheric composition during the polishing process in addition to the roughness. The measurements are carried out with a Perkin Elmer Lambda 950 double-beam spectrophotometer, equipped with the Absolute Reflectance/Transmittance Analyzer (ARTA) motorized goniometer.

Diagnostic ability of EUS-FNA for pancreatic solid lesions with conventional 22-gauge needle using the slow pull technique: a prospective study

Objective. Endoscopic ultrasonography-guided fine needle aspiration (EUS-FNA) using the slow pull technique (SP-FNA) has recently attracted attention as an effective tissue acquisition technique. However, efficacy of SP-FNA with a 22-gauge conventional needle remains unclear. The aim of this study is to evaluate the diagnostic ability of SP-FNA with a 22-gauge needle. Material and methods. Patients with a pancreatic solid lesion were prospectively enrolled in this study. SP-FNA was performed at two needle passes with a 22-gauge needle. One dedicated pathologist evaluated the obtained samples in terms of quantity (Grade 0: scant; Grade 1: inadequate; Grade 2: adequate), quality (Grade 0: poor; Grade 1: moderate; Grade 2: good), and blood contamination (Grade 0: significant; Grade 1: moderate; Grade 2: low), and provided a pathological diagnosis. Additional EUS-FNA was performed by applying suction (SA-FNA). The evaluation points were as follows: diagnostic accuracy of SP-FNA compared with that of SA-FNA, and the quantity, quality, and blood contamination level of SP-FNA-obtained samples. Results. We enrolled 40 cases. The diagnostic accuracy of SP-FNA was 90% (36/40). There was no significant difference in the accuracy between SP-FNA and SA-FNA (90% vs. 90%, p = 1.000). The samples obtained using SP-FNA were assessed as Grade 2 for quantity in 29 cases (73%), quality in 31 (78%), and blood contamination in 25 (63%). Conclusions. Adequate, high-quality, and unsubstantially blood-contaminated samples could be obtained using SP-FNA. The diagnostic ability of SP-FNA was 90%, which appeared to be similar to that of SA-FNA.

Comparison of Total DNA Extraction Methods for Microbial Community Form Polluted Soil

Abstract DNA isolation represents the basic and probably the most important step in molecular biology for microbial strains, and even more, for microbial community analyses. Despite the development of molecular protocols for DNA microbial community isolation, there are still many drawbacks dependent of samples composition, and even the commercially available genomic isolation kits have significant limitations in recovering high genomic DNA amounts, especially from soil samples. Our study is aiming to compare and optimize a total microbial community DNA isolation protocol from polluted soil samples, estimating the amount and the purity of genomic DNA per g of soil, versus time requirements for each protocol, taking under consideration that our soil samples have a high content of humic acids. We checked several protocols for total DNA extraction, CTAB based, including a specific Kit for Soil DNA Isolation Kit NorgenBiotek. We estimated the time needed for each protocol, the amount of the DNA per gram of polluted soil, proteins and RNA contamination grade, by spectrophotometric analysis, but also the grade of PCR amplification inhibition. The most efficient method for our soil samples with high content of humic acid, suitable for further molecular analyses was the total DNA microbial community sample retrieved from Sagova et al. (2008) based protocol, with several adjustments. This protocol will be valuable for molecular analysis on microbial community profiling from environmental samples, especially from polluted soils.

Prospective validation of a surgical complications grading system in a cohort of 2114 patients

BackgroundWe recently reported a grading system for surgical complications. This system proved to have a high sensitivity for recording minor but meaningful complications prolonging hospital stay in patients after colorectal surgery. We aimed to prospectively validate the complication grading system in a general surgery department over 1 year. MethodsAll surgical procedures and related complications were prospectively recorded between January 1st and December 31st, 2009. Surgical complications were graded on a severity scale of 1-5. The system classifies short-term outcome by grade emphasizing intensity of therapy required for treatment of the defined complication. ResultsDuring the study period, 2114 patients underwent surgery. Elective and oncological surgeries were performed in 1606 (76%) and 465 (22%) patients, respectively. There were 422 surgical complications in 304 (14%) patients (Grade 1/2: 203 [67%]; Grade 3/4: 90 [29%]; Grade 5: 11 [4%]).Median length of stay correlated significantly with complication severity: 2.3 d for no complication, 6.2 and 11.8 d for Grades 1/2 and 3/4, respectively (P < 0.001). Older age (OR 2.75, P < 0.001), comorbidities (OR 1.44, P = 0.02), American Society of Anesthesiology score >2 (OR 2.07, P < 0.001), contamination Grade (OR 1.85, P = 0.001), oncological (OR 2.82, P < 0.001), open (OR 1.22, P = 0.03), prolonged >120 min (OR 2.08, P < 0.001), and emergency surgery (OR 1.42, P = 0.02) independently predicted postoperative complications. ConclusionsThis system of grading surgical complications permits standardized reporting of surgical morbidity according to the severity of impact. Prospective validation of this system supports its use in a general surgery setting as a tool for surgical outcome assessment and quality assurance.

Identification of lubricant contamination by biodiesel using vibration analysis and neural network

PurposeThe purpose of this paper is to provide information on lubricant contamination by biodiesel using vibration and neural network.Design/methodology/approachThe possible contamination of lubricants is verified by analyzing the vibration and neural network of a bench test under determinated conditions.FindingsResults have shown that classical signal analysis methods could not reveal any correlation between the signal and the presence of contamination, or contamination grade. On other hand, the use of probabilistic neural network (PNN) was very successful in the identification and classification of contamination and its grade.Research limitations/implicationsThis study was done for some specific kinds of biodiesel. Other types of biodiesel could be analyzed.Practical implicationsContamination information is presented in the vibration signal, even if it is not evident by classical vibration analysis. In addition, the use of PNN gives a relatively simple and easy‐to‐use detection tool with good confidence. The training process is fast, and allows implementation of an adaptive training algorithm.Originality/valueThis research could be extended to an internal combustion engine in order to verify a possible contamination by biodiesel.

Sediment toxicity and deformities of chironomid larvae in Lake Piediluco (Central Italy)

The chemical analysis of the bottom sediments of the Lake Piediluco (Central Italy) has been carried out in order to individuate the potential correlation between the sediment toxicity and the high incidence of mouthpart deformities in chironomid larvae (biological indicators) found in this lake. The environmental contamination has been analyzed by determining the concentrations of the main heavy metals (lead, copper, cadmium, chromium, zinc and nickel), and the concentrations of organic compounds of anthropic source: PAHs, NPPs and OCPs. Heavy metals concentrations have pointed out a non-elevated contamination grade for the Lake Piediluco. The highest level of metals has been detected in the western area that feels the effect of the continuous tributaries incoming load. Also, concerning PAHs, NPPs and OCPs the lake does not present high values of pollution. The highest concentrations of the organic toxicants has been observed in the eastern sector of the lake, which presents typical lentic characteristics. A clear relationship has not found between the toxic substances present in the lacustrine sediments and the deformities incidence for chironomid larvae, which represent an index of environmental alteration. Probably, the mouthpart deformities found in the chironomid larvae of Chironomus plumosus are affected by a synergic action due to the whole toxic mixture present in the sediments of the Lake Piediluco.

Independent Predictors of Treatment Modality for Penetrating Colon Injury.

We aimed to evaluate the independent factors of the treatment of penetrating colon injuries in a teaching and research hospital in light of some of the most commonly cited considerations affecting the decision as to whether to perform primary repair or divert. Hospital records of patients between January 2004 and January 2007 were reviewed retrospectively. Fifty-seven patients were included and divided into two groups. Group A consisted of patients (n = 43) who had primary repair or resection and anastomosis, and Group B consisted of patients (n = 14) who had diverting colostomy. The degree of fecal contamination was assessed by reviewing the detailed operative dictation. The type of colon injury, as determined from the colon injury scale (CIS) of the American Association for the Surgery of Trauma (AAST), and the penetrating abdominal trauma index (PATI) were recorded. Age, sex, presence of shock on admission, location of the injury, and colon-related or non-colonrelated complications between the two groups were not significant. Stab or gunshot injury, operation time, degree of fecal contamination (grade 1/2/3), transfusion, PATI score, hospital stay, and associated organ injury were significantly different in the two groups (p < 0.05). Despite the fact that CIS, fecal contamination, transfusion, PATI and delayed operation affect the decision about the procedure, primary repair can be performed safely on patients with penetrating colon injuries.