Contamination of Honeybee (Apis mellifera L.) Royal Jelly by Pesticides and Sample Preparation Methods for Its Determination: A Critical Appraisal.

Pesticides can easily enter the food chain, harming bee populations and ecosystems. Exposure of beehive products to various contaminants has been identified as one of the factors contributing to the decline in bee populations, and multiple food alerts have been reported. Despite this fact, royal jelly, a valuable bee product with nutritional and functional properties, has received less attention in this context. Pesticide residues of different chemical class can contaminate royal jelly when foraging bees collect pollen or nectar from pesticide-treated flowers, or in some cases, due to its frequent and inappropriate use in the treatment of mites in beehives. To monitor this issue and also make it more reliable, it is crucial to develop effective sample preparation methods for extracting pesticides from royal jelly for subsequent analysis. In this context, this review provides information about sample preparation methods (solid-phase extraction, solvent extraction, and QuEChERS-quick, easy, cheap, effective, rugged and safe) and analytical methods that have been validated or improved to extract and analyze pesticides, respectively, in royal jelly samples of different origins. Finally, future perspectives are discussed. With this background, we aim to provide data that can guide future research related to this topic.

Response Methodology Optimization and Artificial Neural Network Modeling for the Removal of Sulfamethoxazole Using an Ozone-Electrocoagulation Hybrid Process.

Removing antibiotics from water is critical to prevent the emergence and spread of antibiotic resistance, protect ecosystems, and maintain the effectiveness of these vital medications. The combination of ozone and electrocoagulation in wastewater treatment provides enhanced removal of contaminants, improved disinfection efficiency, and increased overall treatment effectiveness. In this work, the removal of sulfamethoxazole (SMX) from an aqueous solution using an ozone-electrocoagulation (O-EC) system was optimized and modeled. The experiments were designed according to the central composite design. The parameters, including current density, reaction time, pH, and ozone dose affecting the SMX removal efficiency of the OEC system, were optimized using a response surface methodology. The results show that the removal process was accurately predicted by the quadric model. The numerical optimization results show that the optimum conditions were a current density of 33.2 A/m2, a time of 37.8 min, pH of 8.4, and an ozone dose of 0.7 g/h. Under these conditions, the removal efficiency reached 99.65%. A three-layer artificial neural network (ANN) with logsig-purelin transfer functions was used to model the removal process. The data predicted by the ANN model matched well to the experimental data. The calculation of the relative importance showed that pH was the most influential factor, followed by current density, ozone dose, and time. The kinetics of the SMX removal process followed the first-order kinetic model with a rate constant of 0.12 (min-1). The removal mechanism involves various processes such as oxidation and reduction on the surface of electrodes, the reaction between ozone and ferrous ions, degradation of SMX molecules, formation of flocs, and adsorption of species on the flocs. The results obtained in this work indicate that the O-EC system is a potential approach for the removal of antibiotics from water.

Concentrations, profiles, emission inventory, and risk assessment of chlorinated benzenes in bottom ash and fly ash of municipal and medical waste incinerators in northern Vietnam.

Concentrations and congener profiles of seven di- to hexachlorinated benzenes (CBzs) were characterized in bottom ash and fly ash samples collected simultaneously from one medical waste incinerator (MEWI) and one municipal waste incinerator (MUWI) in northern Vietnam. Total concentrations of seven CBzs in the fly ash samples ranged from 6.98 to 34.4 (median 19.1) ng g-1 in the MEWI, and ranged from 59.1 to 391 (median 197) ng g-1 in the MUWI. Concentrations of CBzs in the bottom ash samples of the MEWI (median 1.95; range 1.53-5.98 ng g-1) were also lower than those measured in the MUWI samples (median 17.4; range 14.5-42.6 ng g-1). Levels of CBzs in the fly ash samples were significantly higher than concentrations measured in the bottom ash samples, partially indicating the low-temperature catalytic formation of these pollutants in post-combustion zone. In general, higher chlorinated congeners (e.g., hexachlorobenzene, pentachlorobenzene, and 1,2,4,5-tetrachlorobenzene) were more abundant than lower chlorinated compounds. However, compositional profiles of CBzs were different between the ash types and incinerators and even between the same sample types of different sampling days, suggesting that the formation of CBzs in these incinerators is complicated and influenced by many factors. Emission factors and annual emission amounts of CBzs were estimated for the two incinerators by using actually measured data of CBz concentrations in the ash. Daily intake doses and cancer risks of ash-bound CBzs estimated for workers in the two incinerators were generally lower than critical values, but cancer risks caused by other relevant pollutants (e.g., polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and dioxin-related compounds) were not considered.

Microwave-Assisted Synthesis of Goethite Nanoparticles Used for Removal of Cr(VI) from Aqueous Solution.

The microwave-assisted synthesis of goethite nanoparticles has been studied. The samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), differential thermal analysis (DTA) and Brunauer-Emmett-Teller (BET) method. Goethite rod-like nanoparticles have been successfully synthesized in 10 min of microwave treating at 100 °C. Particle size is in the range from 30 to 60 nm in width and from 200 to 350 nm in length. BET analysis indicated that the surface area of the product is 158.31 m²g-1. The feasibility of Cr(VI) removal fromaqueous solution depends on the pH of the solution and contact time. The maximum adsorptionis reached at pH 4.0 and 540 min of contact time. The adsorption kinetics was analyzedby the pseudo-first- and second-order models and the results reveal that the adsorption process obeys the pseudo-second-order model. The adsorption data were fitted well with the Langmuir adsorption isotherm.

Synthesis and Modification of Clinoptilolite.

Clinoptilolite is a natural mineral with exceptional physical characteristics resulting from its special crystal structure, mainstreamed into a large zeolite group called heulandites. An overall view of the research related to the synthesis, modification and application of synthetic clinoptilolite is presented. A single phase of clinoptilolite can be hydrothermally synthesized for 1-10 days in an autoclave from various silica, alumina, and alkali sources with initial Si/Al ratio from 3.0 to 5.0 at a temperature range from 120 to 195 °C. Crystallization rate and crystallinity of clinoptilolite can be improved by seeding. The modification of clinoptilolite has received noticeable attention from the research community, since modified forms have specific properties and therefore their area of application has been broadening. This paper provides a review of the use of organic compounds such as quarter alkyl ammonium, polymer, amine and inorganic species used in the modification process, discusses the processes and mechanisms of clinoptilolite modification, and identifies research gaps and new perspectives.

Robust Matching Cost Function for Stereo Correspondence Using Matching by Tone Mapping and Adaptive Orthogonal Integral Image.

Real-world stereo images are inevitably affected by radiometric differences, including variations in exposure, vignetting, lighting, and noise. Stereo images with severe radiometric distortion can have large radiometric differences and include locally nonlinear changes. In this paper, we first introduce an adaptive orthogonal integral image, which is an improved version of an orthogonal integral image. After that, based on matching by tone mapping and the adaptive orthogonal integral image, we propose a robust and accurate matching cost function that can tolerate locally nonlinear intensity distortion. By using the adaptive orthogonal integral image, the proposed matching cost function can adaptively construct different support regions of arbitrary shapes and sizes for different pixels in the reference image, so it can operate robustly within object boundaries. Furthermore, we develop techniques to automatically estimate the values of the parameters of our proposed function. We conduct experiments using the proposed matching cost function and compare it with functions employing the census transform, supporting local binary pattern, and adaptive normalized cross correlation, as well as a mutual information-based matching cost function using different stereo data sets. By using the adaptive orthogonal integral image, the proposed matching cost function reduces the error from 21.51% to 15.73% in the Middlebury data set, and from 15.9% to 10.85% in the Kitti data set, as compared with using the orthogonal integral image. The experimental results indicate that the proposed matching cost function is superior to the state-of-the-art matching cost functions under radiometric variation.