Optimal Sampling Method Research Articles

Control Parameters Optimization of Accumulator in Hydraulic Power Take-Off System for Eccentric Rotating Wave Energy Converter

To improve the efficiency and stability of an eccentric rotating wave energy converter (ERWEC), the adaptive hydraulic power-take-off (PTO) system with an accumulator is designed and developed. Experiments are performed to analyze the effects of trigger pressure, delay time, and open state duration on average output power and power fluctuation index. The results show that the effects of those three control parameters of accumulator on output power are strongly coupled. The experimental examples are designed based on the optimal Latin hypercube sampling (OLHS) method, and the nonparameterized agent models of control parameters to output power indices are established based on the Gaussian process regression (GPR) method. With the help of sensitivity analysis, it is found that the coupled effect of delay time and open state duration on the power fluctuation index is greater than that on the average output power. Furthermore, the optimal combination of control parameters is obtained by non-dominated sorting genetic algorithm-III (NSGA-III), which improves the amount and stability of output power from a hydraulic PTO system. This paper is of important significance for parameter setting of hydraulic PTO systems with an accumulator for wave energy converter, and provides the basis for the real-time adjustment of control parameters under complex sea conditions.

Crop-Specific Effects on Pan-Trap Sampling of Potential Pollinators as Influenced by Trap Color and Location

Characterizing insect communities in pollinator-dependent crops helps determine the potential pollinator effectiveness and their effects on crop yield. Few studies have examined pollinator communities and their services to crops in South America. Furthermore, optimal sampling methods for these communities in the crop habitat have received little attention. Pan traps are one of the simplest and most widely used sampling methods to assess insect diversity. We compared different pan trap arrangements to describe potential pollinator communities in two commercial crops (blueberry and canola) in Southern Chile. We compared communities in the crops and assessed how sampling position (border or center) and pan trap color (blue, white, or yellow) affected sample composition. Species composition was significantly different between crops. Furthermore, trap color affected sample composition in blueberry, but trap position did not, whereas color had no significant effect on canola, but trap position did. In all cases, yellow pans captured the largest number of species. Hymenoptera explained most of the differences in sampling efficiency because of the differential responses across species. We suggest that pan trap assessments of the diversity in potential pollinator insects depend on crop characteristics, including planting configuration and floral morphology. Therefore, comparative studies should include pans of different colors positioned at various locations within the crop.

Evaluation of the optimal sampling approach for HPV genotyping in circumcised heterosexual men with genital warts

BackgroundHuman papillomavirus (HPV) causes a serious socioeconomic burden globally. However, there is currently no consensus on the optimal sampling method for HPVDNA genotyping in circumcised heterosexual men. This study aimed to determine the diagnostic efficacy of 6 different anatomic sampling sites in HPV DNA polymerase chain reaction (PCR) testing of circumcised heterosexual men with genital warts. MethodsThe study included circumcised heterosexual men who presented to our clinic with complaints of genital warts. Swab samples were obtained from the penile shaft (PS), scrotum, coronal sulcus (CS), and external urethral meatus (EUM). First-void urine (FVU) and genital wart biopsy (GWB) were also tested for HPV DNA by PCR. ResultsA total of 32 patients (mean age: 36.9 ± 6.9 years) were included. None of the six samples studied was sufficient on its own to reveal all HPV types detected in a patient. When the samples were analyzed individually, GWB detected an average of 49.5% of total HPV types in a patient. This rate was 50.5% for PS, 40.4% for CS, 31.6% for scrotum, 26.3% for EUM, and 15.8% for FVU samples. The detection rate increased to 75.8% with combined testing of GWB and PS samples, 83.2% with GWB/PS/CS, 90.5% with GWB/PS/CS/scrotum, and 98.9% with GWB/PS/CS/scrotum/EUM samples. ConclusionNo single anatomic region or sample type can detect all HPV types present in circumcised heterosexual men by PCR assay. The detection rate approaches 99% when wart biopsy is combined with swab sampling of the penile shaft, coronal sulcus, scrotum, and external urethral meatus.

A memetic algorithm for finding multiple subgraphs that optimally cover an input network.

Finding dense subgraphs is a central problem in graph mining, with a variety of real-world application domains including biological analysis, financial market evaluation, and sociological surveys. While a series of studies have been devoted to finding subgraphs with maximum density, the problem of finding multiple subgraphs that best cover an input network has not been systematically explored. The present study discusses a variant of the densest subgraph problem and presents a mathematical model for optimizing the total coverage of an input network by extracting multiple subgraphs. A memetic algorithm that maximizes coverage is proposed and shown to be both effective and efficient. The method is applied to real-world networks. The empirical meaning of the optimal sampling method is discussed.

Optimal sampling and analysis methods for clinical diagnostics of vaginal microbiome

Next-generation sequencing-based microbiological analysis is a complex way to profile vaginal microbiome samples since each step affects the results gained. Methodologies for sample collection lack golden standards. We compared Puritan DNA/RNA swab (PS) and Copan FLOQ swab (CS) and provided consistent and reliable microbiome profiles analyzed by 16S rRNA gene sequencing. We collected two consecutive vaginal samples utilizing PS with room temperature storing and CS with instant freezing from 26 women. Variable region 4 of bacterial 16S rRNA gene was amplified with single PCR by custom-designed dual-indexed primers and sequenced with Illumina MiSeq system. Read quality control, operational taxonomic unit tables, and alpha and beta diversities analysis were performed, and community richness, diversity, and evenness were evaluated and compared between the two samplings and tests. Nineteen sample pairs produced detectable, intact DNA during the extraction protocol and/or further microbial profiles. Alpha bacterial diversity indices were independent on the collection protocol. No significant statistical differences were found in the measured beta diversity metrics between the collection methods. Of the women, 43% had Lactobacillus-dominated vaginal microbiome profile despite of collection method. Previously reported important vaginal microbiome phyla Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and Proteobacteria were present in the sample set although their relative abundances varied among individuals. PS and CS enable constant vaginal microbiota sampling. The PS method with no need for instant freezing is suitable for on-site collections at clinics. Furthermore, it seems to be possible to take two samples instead of one with constant microbiological results.

공공하수처리시설 단위공정별 고장예지 알고리즘 개발

In order to develop an automatic control system for public sewage treatment facilities, it is necessary to conduct a technical analysis of each water quality measurement item to discover new trends or patterns. In this study, a failure prediction algorithm for each instrument or unit process was developed for the automatic control of public sewage treatment facilities, with the optimal data sampling method and abnormality detection criteria for each water quality item. In order to establish the confidence intervals for the five telemonitoring systems (TMS) parameters (chemical oxygen demand, suspended solids, total nitrogen, total phosphorus, and pH) in the sedimentation tank and bioreactor, that during a set period, 48, 72, or 168 samples were taken and the error rate was reviewed. Based on this, 48 samples were established as the optimal level with an error rate of 1.46%. In addition, the abnormality rate for the TMS data at a confidence interval of μ±3σ averaged 1.73%, confirming that any abnormalities that were recorded were not solely the result of simple data errors but also included genuine problems with an instrument or unit process.

Hyaluronic acid skin penetration evaluated by tape stripping using ELISA kit assay

Hyaluronic Acid (HA) is an endogenous skin matrix component with moisturizing and anti-inflammatory and healing properties. Cosmetic formulations containing HA aim to enhance skin structure, hydrate skin and reduce wrinkles. Therefore, the skin diffusion of HA into stratum corneum after application of a formulation containing two different size of HA, High Molecular weight (HMW-HA) and Low Molecular Weight (LMW-HA)) was evaluated. Ex vivo human skin samples were used to validate an ELISA assay measuring HA in the stratum corneum (SC), viable epidermis and dermis, and to identify optimal washing and extraction methods. These methods were used to measure HA levels in the SC of subjects before and after daily topical application of an HA-containing formulation for 7 days. Samples of SC (5 tape strips) were taken before and 2 h after the application on D0, D1 and D7. The ELISA assay was suitable for measuring HA in the SC but not epidermal or dermal layers. The upper and lower limits of quantitation were the same for both sizes of HA (200 and 3.1 ng/ml, respectively). In both ex vivo human skin and human volunteers, the “dry method” of removing the formulation led to much higher levels of HA in the SC samples, whereas the “wet method” involving one cotton swab soaked with an aqueous solution containing 10% soap and a second cotton swab for drying, was effective in removing the formulation and more relevant to simulate washing/showering. In the clinical study, the amount of HA in SC layers 3–5 were used to represent the HA level in the SC, whereas layers 1 and 2 were considered as surface “residual film”. After each application, there was a significantly higher amount of HA compared to the amount before application, which was observed using both wash methods. The residual level 24 h after the first application was at least 8 times higher than before the first application and at least 31 times higher after 7 applications. In conclusion, these investigations validated the use of the ELISA method for the measurement of HA in SC samples. The ex vivo experiments provided recommendations for the clinical study, including the preferred cleansing and optimal sampling methods. The clinical study demonstrated the diffusion, accumulation and maintenance of HA levels in the SC after repeated application of the formulation containing HMW-HA and LMW-HA.

Projecting Compound Flood Hazard Under Climate Change With Physical Models and Joint Probability Methods

AbstractAccurate delineation of compound flood hazard requires joint simulation of rainfall‐runoff and storm surges within high‐resolution flood models, which may be computationally expensive. There is a need for supplementing physical models with efficient, probabilistic methodologies for compound flood hazard assessment that can be applied under a range of climate and environment conditions. Here we propose an extension to the joint probability optimal sampling method (JPM‐OS), which has been widely used for storm surge assessment, and apply it for rainfall‐surge compound hazard assessment under climate change at the catchment‐scale. We utilize thousands of synthetic tropical cyclones (TCs) and physics‐based models to characterize storm surge and rainfall hazards at the coast. Then we implement a Bayesian quadrature optimization approach (JPM‐OS‐BQ) to select a small number (∼100) of storms, which are simulated within a high‐resolution flood model to characterize the compound flood hazard. We show that the limited JPM‐OS‐BQ simulations can capture historical flood return levels within 0.25 m compared to a high‐fidelity Monte Carlo approach. We find that the combined impact of 2100 sea‐level rise (SLR) and TC climatology changes on flood hazard change in the Cape Fear Estuary, NC will increase the 100‐year flood extent by 27% and increase inundation volume by 62%. Moreover, we show that probabilistic incorporation of SLR in the JPM‐OS‐BQ framework leads to different 100‐year flood maps compared to using a single mean SLR projection. Our framework can be applied to catchments across the United States Atlantic and Gulf coasts under a variety of climate and environment scenarios.

Multi-objective optimization of the geometric parameters of a pressure-swirl nozzle

ABSTRACT The geometric parameters of the pressure-swirl nozzle demonstrate a significant effect on the atomization performance such as the spray cone angle and mass flow rate. However, these objectives are incompatible, and obtaining a nozzle geometric parameter that optimizes all the atomization performances is difficult. The effectiveness of the nozzle optimization process is typically low, resulting in high costs. To this purpose, an enhanced CBSO-Kriging surrogate model was developed to solve this expensive black box problem, and the spray cone angle and mass flow rate were optimized using a multi-objective optimization algorithm. Firstly, the optimal Latin hypercube sampling method was used to generate 65 sets of sample points, and the corresponding response values were calculated using CFD simulation. The established surrogate model of atomization performance can predict the atomization characteristics of the nozzle with arbitrary shape. The correlation between the key geometric parameters and the spray cone angle and the mass flow rate was determined on this basis. Then, to find the optimal geometric parameters for the nozzle, the NSGA-II algorithm was used. In comparison to the initial model, the optimization results show that the spray cone angle and mass flow rate increased by 4.26% and 37.74%, respectively.

Evaluation of Recycled Spent Coffee Material Treated with Animal Glue, Starch, and Red Clay as Acid Materials

Annual coffee consumption has increased to 10 million tons. Of the coffee consumed, 65% is discarded as spent coffee grounds (SCG). However, most SCG are buried in the ground as organic waste. The more coffee consumption increases, the more land is used for disposing of spent coffee. SCG recycling has gotten considerable attention as a solution involved in these issues. The construction community has studied means and methods to recycle SCG as construction materials, such as bricks, subgrade fillers, thermal insulators, etc. This paper presents a new method, which recycles SCG as a construction material, maximally using its acidity. The SCG were hardened with natural binders (i.e., animal glue (AG) and starch (S)) and red clay (RC). The SCG mixtures were pressed with 2 MPa in a cylindrical mold and cured for 7 days. Then, the strength, durability, and pH tests were measured. The AG- and RC-treated SCG sample, which outputs 1933 kPa of strength and a 4.9 pH value, is identified as the optimal sampling method among the acid materials produced in this study. The optimal sample decreases the pH to approximately 7 of water where 68% weight of Ordinary Portland cement was soaked in.

Multi-objective optimization of a novel vortex finder for performance improvement of cyclone separator

This study proposed a multi-objective optimization of novel vortex finder, called Slotted Vortex Finder (SVF), applied in the Stairmand cyclone separator, to obtain a most appropriate geometric configuration for performance improvement as the Stairmand cyclone separator had been widely used in industry for dust removal since last century. The Optimal Latin Hypercube Sampling (OLHS) method was utilized to conduct design of experiment for four significant design variables, including slot number (Ls), slot length (N), span angle (α) and inclination angle (β). Computational Fluid Dynamics (CFD) and Response Surface Model (RSM) were adopted to get precise output response and construct accurate fitness functions between design variables and objectives. Multi-objective Genetic algorithm was employed to find out the best solution with maximum collection efficiency and minimum Euler number based on the well-constructed fitness functions. The finally selected optimal model provided Euler number reduction of 34.51%, collection efficiency increasing of 4.32% and cut off size reduction of 5.53%, compared with original model. The obtained optimal geometry shape of novel vortex finder could be used as an effective reference for industrial factories to gain enough considerable cyclone performance improvement and high economic benefits by making only small modifications on the in-using cyclone separator. • A novel and efficient structure of slotted vortex finder was demonstrated and discussed. • Surrogate model was utilized to evaluate the effect of geometric design variables. • Multi-objective optimization of slotted vortex finder was conducted. • The optimal solution of slotted vortex finder is meaningful and promising for industrial application.

Comparable Detection of SARS-CoV-2 in Sputum and Oropharyngeal Swab Samples of Suspected COVID-19 Patients

The accurate detection of SARS-CoV-2 through respiratory sampling is critical for the prevention of further transmission and timely initiation of treatment. There is a diverse range of SARS-CoV-2 detection rates in reported studies, with uncertainty regarding the optimal sampling method for COVID-19 diagnosis and monitoring. Oropharyngeal sampling (OPS) is one of the most commonly used methods of respiratory sampling in Ghana and other parts of the world for the detection of SARS-CoV-2 viral RNA. However, this sampling technique has a number of drawbacks, which include difficulty in obtaining high-quality swab samples, increased risk of infection to healthcare workers, and increased cost from a regular supply of swabs, transport media, and personal protective equipment (PPE). This study, therefore, sought to evaluate the diagnostic performance of sputum specimens in the diagnosis of COVID-19. This was a cross-sectional analytical study conducted in two health facilities in Kumasi, Ghana, between April and September 2021. Paired samples (an oropharyngeal swab and sputum) were taken from each recruited patient and run concurrently for the detection of SARS-CoV-2 genes (the N and ORF1ab genes) using RT-qPCR. Of the 317 patients recruited, 50.8% were males, and 60.4% were young adults aged 20–39 years. A significant proportion (65.9%) of the patients did not have any co-morbidity, and the majority were with symptoms; predominantly cough (36.3%), headache (31.5%), general weakness (24.0%), fever (20.2%), and sore throat (16.1%). Being symptomatic (p = 0.003), having comorbidity (p = 0.001), and the reporting facility (p = 0.010) were significantly associated with the COVID-19 status. The sputum samples yielded more COVID-positive, 120/317 (37.9%), as compared to OPS, 83/317 (26.2%). The sputum samples were 85.5% (95% CI, 76.4–91.5) sensitive, 79.1% (95% CI, 73.4–83.7) specific, and with positive and negative predictive values of 59.2% and 93.9%, respectively, when compared with OPS. The overall median of the SARS-CoV-2 viral loads for sputum (3.70 × 103 copies/mL) were significantly higher than in OPS (1.18 × 102 copies/mL) (p = 0.003). Findings from the study suggest self-collected sputum as a useful alternative to OPS for the diagnosis of COVID-19, providing a comparable diagnostic performance and, thereby, easing the uncomfortable process and mitigating risk of aerosol transmission to healthcare workers.

Identification of nonparametric thermodynamic model and optimization of ocean thermal energy conversion radial inflow turbine

Turbine is one of the key components of ocean thermal energy conversion system, and its aerodynamic performance and geometric structure directly affect the performance of the system. At present, the design methods of radial inflow turbines can be roughly divided into three categories: trial method, best velocity ratio method and screening method, which follow no concrete rules and are not comprehensive, and rely mostly on the designers' experience. This study proposes a fully data-based non-parametric model identification and optimization method for ocean thermal energy conversion radial inflow turbines is proposed, and takes the 25 kW R134 working fluid turbine of the ocean thermal energy conversion system as an example for verification and analysis. First, the optimal Latin hypercube sampling method was used to complete the experimental design with seven initial thermodynamic parameters as independent variables. And then according to the test data and the Gaussian process regression identification, the non-parametric turbine thermodynamic model was obtained. At last, on the basis of this model, the NSGA-III multi-objective optimization algorithm was used to optimize the design with the goal to achieve maximum efficiency and minimum diameter, and the optimized results were obtained. The results show that the non-parametric model based on the Gaussian process proposed in this study has higher accuracy, and the optimization results obtained based on this model are more efficient and have a more compact structure. The research work described in this study saves time and cost for completing the aerodynamic performance design of the turbine and further improving the expansion efficiency of the radial inflow turbine. It is of great significance for the practical application of promoting ocean thermal energy conversion.

Optimization of the impeller for hydraulic performance improvement of a high-speed magnetic drive pump

Magnetic drive centrifugal pumps have compact structure and lower efficiency than ordinary centrifugal pumps. The surrogate-based optimization technique was applied to improve the performance of a high-speed magnetic drive pump with the help of numerical simulations. Eight geometrical parameters of the impeller were considered as the design variable. About 290 samples of impeller were generated by optimal Latin hypercube sampling (OLHS) method, and the corresponding efficiencies of all the impeller samplings were obtained from numerical simulation. The performance test of the prototype pump was carried out, and the experimental results were in good agreement with the numerical simulation results. The hydraulic efficiency at 1.2 Qd of the magnetic drive pump was set as the optimization objective. Using response surface methodology (RSM), surrogate models were established for the objective functions based on the numerical results. The multi-island genetic algorithm (MIGA) was used to optimize the impeller. The hydraulic efficiency of the optimal impeller at rated flow rate was 72.89%, which was 6.23% higher than the prototype impeller.

Critical issues in pathologic evaluation of pancreatic ductal adenocarcinoma resected after neoadjuvant treatment: a narrative review.

Preoperative neoadjuvant therapy (NAT) is increasingly used in the treatment of patients with potentially resectable pancreatic ductal adenocarcinoma (PDAC). Because NAT often induces heterogeneous tumor response and extensive fibrosis both in tumor and adjacent pancreatic tissue, pathologic assessment of posttherapy pancreatectomy specimens is challenging. A limited number of studies examined the optimal grossing and sampling methods, tumor response grading (TRG), and the prognostic value of posttherapy tumor (ypT) and lymph node (ypN) stages of treated PDAC patients. In this review, we will provide an overview of the current status and critical issues in pathologic evaluation of PDAC resected after NAT. In PubMed, Google Scholar and Web of Science, we reviewed existing English literature (published up to December 2021) highlighting the most recent ones using electronic databases and authors' experience to outline the challenging aspects and new perspectives on pathologic assessment of the treated PDAC. The recent recommendations from the Pancreatobiliary Pathology Society (PBPS) provide the much-needed guidelines for systematic and standardized pathologic evaluation and reporting of treated PDAC for optimal patient care. For treated PDAC, tumor size measured by gross and radiology is not reliable. Histologic validation of tumor size on consecutive mapping sections is recommended for accurate ypT stage. A tumor size of 1.0 cm seems to be a better cutoff for ypT2 for treated PDACs. The published data suggested that the MD Anderson Cancer Center (MDA) TRG system is easy to use, has a better interobserver agreement and better correlation with patient prognosis compared to the College of American Pathologists (CAP) and Evans grading systems and may be used as an alternative TRG system for the CAP cancer protocol. Systemic and standardized grossing and sampling are essential for accurate pathologic evaluation and reporting for optimal care of PDAC patients who received NAT. Future studies on optimal sampling and integration of histopathology with artificial intelligence (AI), molecular and immunohistochemical markers are needed for better and personalized care of treated PDAC patients.

Optimization strategy for curing ultra-thick composite laminates based on multi-objective genetic algorithm

Thermal gradient and temperature overshoot during the curing process of ultra-thick carbon fibre composite have a major impact on its properties. We present a strategy to optimize the curing process based on the surrogate model and genetic algorithm. Firstly, a FE model based on heat transfer was developed for curing a 30 mm thick laminate and validated by experimental data. Then a multi-objective optimization strategy was developed by combining the optimal Latin hypercube sampling method, elliptical basis function (EBF) neural network model and non-dominated sorting genetic algorithm-II (NSGA-II). It is found that the optimized cure cycle can effectively reduce the undesirable maximum DoC (Degree of cure) gradient and the temperature gradient leading to improved mechanical properties for the 30 mm thick laminate.

Multi-objective optimization of a bow thruster based on URANS numerical simulations

In this study, a multi-objective design optimization of a bow thruster, which involved both experimental and numerical analyses, was performed. By changing the chamfer form at the tunnel opening of the bow thruster and the position of the anti-suction tunnel, the optimization procedure aimed to improve the propulsion efficiency, reduce the amplitude of the fluctuating pressure on the tunnel wall, and balance the pressure difference on the hull caused by the speed. First, model tests were conducted to measure the thrust and torque of the bow thruster as well as the fluctuating pressure acting on the tunnel. Numerical simulations were also performed under the same conditions based on the unsteady Reynolds-averaged Navier-Stokes (URANS) method. The accuracy of the numerical results was verified by comparison with the experimental data. Second, the chamfer depth and angle of the tunnel opening and the distance between the anti-suction tunnel and the propeller axis in the length and height directions were taken as the design variables. A sample set that contained 30 sampling points was selected using the optimal Latin hypercube sampling (opt-LHS) method. A surrogate model was built based on the Support Vector Regression (SVR) algorithm, and the multi-island genetic algorithm was utilized during the tuning process of the surrogate model parameters. On this basis, the non-dominated sorting genetic algorithm II (NSGAII) was used for the three-objective optimization and the Pareto solution set was obtained. Due to the inverse relationship between the propulsion efficiency and the fluctuating pressure amplitude, four optimal solutions were selected from the Pareto optimal solution set, and direct numerical computations were conducted to verify the optimization results. The results showed that, compared with the original shape, the fluctuating pressure amplitudes for the four optimal solutions were reduced significantly after the optimization, with a maximum reduction of 18.56%, but their propeller propulsion efficiencies were slightly lower than the original hull. Increasing the chamfer angle and depth significantly reduced the flow-separation area around the tunnel entrance, but it correspondingly increased the flow velocity in the tunnel, which caused the propeller to not work at its highest efficiency point; thus, the propulsion efficiency was reduced to a certain extent. Moreover, the position of the anti-suction tunnel could be determined using the SBD method, but with an increase in the chamfer angle, the location where the jet of the bow thruster re-attached to the hull after mixing with the external flow moved towards the stern. This led to an expansion of the low-pressure area near the rear of the tunnel that correspondingly increased the pressure difference on the hull. If the chamfer angle was large enough, although the pressure difference could be reduced to a fairly low value through the anti-suction tunnel, it could not be balanced completely.

Determination of zinc by atomic absorption in automobile tire rubber as a source of ecotoxicants in atmospheric air

Annotation. A methodology for determining zinc in tires (as a source of ecotoxicants in the atmospheric air) by atomic absorption with microwave pre-treatment as a product of motor vehicle wear in St. Petersburg was developed. In the article, the author gives different ways of sampling for testing. One of the rubber samples was taken from one area no larger than 5x5 cm on one tyre (first sampling option), the second sample was taken cumulatively from all tyre sides around its circumference (second sampling option). Tests of selected samples were carried out allowing conclusions to be drawn about the optimal sampling method. A comparative analysis has been made of the test results of samples taken by different methods from the car tyre surface. Based on the comparative analysis conclusions were made about the homogeneity of the tire composition. Various physical and chemical methods of sample preparation for the heavy metals determination are presented. In the course of the work the author selected the optimal conditions for sample preparation for testing allowing to obtain the maximum possible extraction of the analyte at the stage of sample preparation. The atomic absorption method was used to determine the zinc content in automobile tire samples. On the basis of the results obtained conclusions about the optimal sampling methods and sample preparation were made and the test conditions of the samples were optimized.

Determination of zinc by atomic absorption in automobile tire rubber as a source of ecotoxicants in atmospheric air

Annotation. A methodology for determining zinc in tires (as a source of ecotoxicants in the atmospheric air) by atomic absorption with microwave pre-treatment as a product of motor vehicle wear in St. Petersburg was developed. In the article, the author gives different ways of sampling for testing. One of the rubber samples was taken from one area no larger than 5x5 cm on one tyre (first sampling option), the second sample was taken cumulatively from all tyre sides around its circumference (second sampling option). Tests of selected samples were carried out allowing conclusions to be drawn about the optimal sampling method. A comparative analysis has been made of the test results of samples taken by different methods from the car tyre surface. Based on the comparative analysis conclusions were made about the homogeneity of the tire composition. Various physical and chemical methods of sample preparation for the heavy metals determination are presented. In the course of the work the author selected the optimal conditions for sample preparation for testing allowing to obtain the maximum possible extraction of the analyte at the stage of sample preparation. The atomic absorption method was used to determine the zinc content in automobile tire samples. On the basis of the results obtained conclusions about the optimal sampling methods and sample preparation were made and the test conditions of the samples were optimized.

Observing Brief and Irregular Behaviour of Animals—The Validity of Short Observation Periods

There are efficient sampling methods to accurately estimate behaviour with a moderate or long duration. For short behaviour, observing animals continuously is recommended although there is no recommended minimum observation time. In most studies, sampling method and observation time per day is determined by practical considerations. Thus, this study analysed the validity of behavioural observations in different observation periods using continuous sampling (CS) or time sampling (TS) based on biting behaviour. Tail-biting and ear-biting of weaned piglets in six pens were continuously observed for 12 h per day for 4 days to form a reference. Shorter observation periods of CS and TS were simulated by taking subsets of this reference. The amount of behaviour per hour of each observation period was compared to the reference and to other observation period of the same kind and length. Four different measurements were defined to calculate accuracy scores (AS; 0–1; higher values are better). Comparison to the reference shows better AS for observation periods with longer observation time in total (0.5 h of CS: 0.2; 6 h of CS: 0.6). Additionally, TS covers longer time periods without decreasing AS. However, focus on activity time results in an overestimation of irregular behaviour. Comparing AS among observation periods of the same kind and length show overall low agreement. This study indicated problems of different observation periods of CS and TS to accurately estimate behaviour. Therefore, validity of behavioural observations should be analysed in greater detail to determine optimal sampling methods.