Particulate Matter Inhalation Exposure Chambers and Parameters Affecting Their Performance: A Systematic Review Study

Exposure to inhalation aerosols and particulate matter (PM) in different concentrations can increase the risk of respiratory, cardiovascular, and other related diseases. The inhalation exposure studies are implemented to assess the biological effects of these hazardous agents in human or animal models, in whole-body (WB) or nose/head-only conditions. Several factors can affect the performance of the inhalation exposure chambers and if left uncontrolled, the results may not be desirable. The current study reviewed the characteristics, structures, and factors affecting the performance of the WB chambers, especially the ones designed for small animal exposure to the PM. At the primary stage, the criteria and the search strategy were determined and the keywords were searched in the scientific electronic databases. Totally, 1051 articles were extracted in the first stage, and finally seven articles were adopted. The technical and design details, materials, coefficient variations (CVs) of concentration, assessment methods, type and number of laboratory animals, procedure, and animals housing conditions were extracted from the selected articles. Then the most desirable WB inhalation exposure chamber was determined based on the criteria for assessing the presented exposure chambers such as the animal housing and least CVs of the concentration in the respiratory zones of the animals under study. It was concluded that the Kimmel design was the best and the most desirable chamber structurally and geometrically, since the concentration of the particle (NaCl) injected into the chamber varied from 3.5% to 5.2%, under standard conditions. Keywords:Inhalation Chamber; Whole-Body; Inhalation Exposure; Particulate Matter

Structural Modeling of Safety Performance in Construction Industry

Background: With rapid economic development and industrialization, the construction industry continues to rank among the most hazardous industries in the world. Therefore, construction safety is always a significant concern for both practitioners and researchers. The objective of this study was to create a structural modeling of components that influence the safety performance in construction projects. Methods: We followed a two-stage Structural Equation Model based on a questionnaire study (n=230). In the first stage, we applied the Structural Equation Model to the proposed model to test the validity of the observed variables of each latent variable. In the next stage, we modified the proposed model. The LISREL 8.8 software was used to conduct the analysis of the structural model. Results: A good-fit structural model (Goodness of Fit Index=0.92; Root Mean Square Residual=0.04; Root Mean Square Error of Approximation=0.04; Comparative Fit Index=0.98; Normalized Fit Index=0.96) indicated that social and organizational constructs influence safety performance via the general component of the safety climate. Conclusion: The new structural model can be used to provide better understanding of the links between safety performance indicators and contributing components, and make stronger recommendations for effective intervention in construction projects

Modeling the concentration of suspended particles by fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS) techniques: A case study in the metro stations

Background: Today, the usage of artificial intelligence systems and computational intelligence is increasing. This study aimed to determine the fuzzy system algorithms to model and predict the amount of air pollution based on the measured data in subway stations. Methods: In this study, first, the effective variables on the concentration of particulate matter were determined in metro stations. Then, PM2.5, PM10, and total size particle (TSP) concentrations were measured. Finally, the particles’ concentration was modeled using fuzzy systems, including the fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS). Results: It was revealed that FIS with modes gradient segmentation (FIS-GS) could predict 76% and ANFIS-FCM with modes of clustering and post-diffusion training algorithm (CPDTA) could predict 85% of PM2.5, PM10, and TSP particle concentrations. Conclusion: According to the results, among the models studied in this work, ANFIS-FCM-CPDTA, due to its better ability to extract knowledge and ambiguous rules of the fuzzy system, was considered a suitable model

Route exposure and adverse effects monitoring of Aflatoxin B1 in the workers of wet waste management, the role of body redox system modulation

Exposure to dust, containing different fungi metabolites such as aflatoxins is a risk factor for developing liver and kidney health abnormalities. Occupational evaluation of the aflatoxin's exposure-induced health abnormalities should include the monitoring of bioaerosols in the workplace and personal air, and applying of appropriate blood biomarkers to assess Aflatoxin B1 (AFB1) detrimental effects on a worker’s health. However, to the best of our knowledge, these appropriate methods, especially determining the associated-adverse effects on health, following exposure, haven't been well documented in the literature at the wet waste handling sites. In the current study, the AFB1 quantity in the area, personal, and settled dust in wet household waste handling samples and AFB1-Albumin levels in the serum of workers in comparison with the control group were determined using high-pressure liquid chromatography with a fluorescent detector (HPLC-FLD) methods. Moreover, the adverse effects of AFB1 on the liver and kidney biochemical profiles of the exposed workers and its relation to antioxidant capacity in the household wet waste sorting were recorded in a consolidated investigation. The results demonstrated that the average airborne dust concentration and its associated AFB1 content were significantly higher in wet waste management sections as compared to the control place, corresponding to the serum AFB1-Albumin levels of workers. Furthermore, AFB1-induced changes in the serum biochemicals evaluating liver and kidney function tests and antioxidant profiles of workers in wet waste handling sections were indicative of their function abnormalities. The results imply AFB1-induced adverse effects on the liver and kidney functions may be mediated through the body redox system modulation

Carbendazim trace analysis in different samples by using nanostructured modified carbon paste electrode as voltametric sensor

Carbendazim (CBZ) as a fungicide is widely used to control fungal diseases in agriculture, veterinary medicine, and forestry. In this study, molecularly imprinted nano-size polymer was synthesized and then combined with multiwalled carbon nanotubes to be used as modifiers for carbon paste electrode to detect carbendazim in water, fruit, agricultural wastewater, and urine samples by using the square-wave technique. Some common ions and pesticides were investigated as interferences in analyte, to study the sensitivity and selectivity of the modified carbon paste electrode for carbendazim. The combination of molecular imprinted polymer and multiwalled carbon nanotubes showed a significant increase in peak current in electrocatalytic activity on electrochemical detection of the carbendazim. The linear range of 1 × 10−10 to 5 × 10−8molL−1 was investigated. The lower detection limit was determined to be 0.2 × 10−10molL−1, and the relative standard deviation for the target molecule analysis was 2.07%. The result reveals that the modified carbon paste sensor with Multi walled Carbon Nanotubes (MWCNTs) and Molecular Imprinted Polymer (MIPs) can be used easily, without preparation steps that have high selectivity and sensitivity to determine carbendazim in water, fruit, agricultural wastewater, and urine samples

Factors Influencing Unsafe Behaviors and Accidents on Construction Sites: A Review

Objective. Construction is a hazardous occupation due to the unique nature of activities involved and the repetitiveness of several field behaviors. The aim of this methodological and theoretical review is to explore the empirical factors influencing unsafe behaviors and accidents on construction sites. Methods. In this work, results and findings from 56 related previous studies were investigated. These studies were categorized based on their design, type, methods of data collection, analytical methods, variables, and key findings. A qualitative content analysis procedure was used to extract variables, themes, and factors. In addition, all studies were reviewed to determine the quality rating and to evaluate the strength of provided evidence. Results. The content analysis identified 8 main categories: (a) society, (b) organization, (c) project management, (d) supervision, (e) contractor, (f) site condition, (g) work group, and (h) individual characteristics. The review highlighted the importance of more distal factors, e.g., society and organization, and project management, that may contribute to reducing the likelihood of unsafe behaviors and accidents through the promotion of site condition and individual features (as proximal factors). Conclusion. Further research is necessary to provide a better understanding of the links between unsafe behavior theories and empirical findings, challenge theoretical assumptions, develop new applied theories, and make stronger recommendations

Preparation of novel nano–based films impregnated by potassium permanganate as ethylene scavengers: An optimization study

Potassium permanganate (KMnO4) is a dominant ethylene (C2H4)-scavenger extensively used in fresh horticultural commodities, mainly in climacteric fruit, to prolong their shelf life. This material has been traditionally utilized as a C2H4-permeable sachet for inclusion into packages of produces. New formulation strategies are required in polymeric materials to develop nanocomposites with ethylene scavenging potential, as well as good barrier and mechanical properties. This work involved preparation and optimization of novel interesting nanocomposites based on polyolefin elastomer (POE) comprising impregnated nanoparticles (nanosilica (NS) and nanoclay (NC)) with KMnO4 via the response surface methodology (RSM). Regression models were developed for water vapor permeability (WVP), ethylene absorbency (EA), and mechanical properties as a function of concentrations of independent variables (POE-g-MAH (0–3%), NS (0–1.5%), NC (0–2%)). According to Field emission-scanning electron microscopy (FE-SEM) and X-ray diffraction (XRD) analysis results, both NS and NC were fully dispersed in the POE matrix. The prepared nanocomposites demonstrated enhanced mechanical properties, larger EA, and lower WVP than neat POE film did. Ethylene absorption capacity increased at higher concentrations of impregnated nanoparticles due to their higher KMnO4 concentration. In addition, the optimized nanocomposite films were shown to extend the shelf life of bananas up to 15 days at ambient conditions

The voltammograms of MWCNTs-MIP-CPE, MWCNTs-NIP-CPE, and CP for CBZ sensor in CBZ 1.0×10⁻⁷ mol mol<i>L</i>⁻¹.

(Supporting electrolyte: phosphate buffer 0.1mol molL−1) (Scan rate: 100 mV/s).</p