Assessment Scheme Research Articles

Prioritizing Management of Invasive Alien Species of EU Concern—A Northern Perspective

Invasive alien species (IAS) represent one of the major threats to biodiversity globally. Each member state in the EU is required to compile a management plan for IAS of Union concern. This requires risk assessments to prioritize management measures consistent with the requirements of each EU member state. Here, we review the management priorities for the 88 IAS of Union concern based on the risk assessment scheme developed for Finland. Of 88 species, 52 had not been detected in Finland and 51 species were categorized as species that fail to succeed in Finland. Climatic conditions can be regarded as a major factor limiting the success of those species. Five primary management categories were recognized. Monitoring was deemed the primary management option for 30 species, prevention of entry into Finland for 30 species, prevention of escape into nature for 17 species, prevention of further spread and/or the management of areas with high biodiversity value for 4 species and eradication for 7 species. It is concluded that national management plans should consider local environmental conditions and adjust management options according to national risk assessments.

Disaster Risk Assessment Scheme—A Road System Survey for Budapest

This study presents a method to analyze the most critical elements of the public road system concerning outer effects which hinder the normal operation of the whole system. The surveyed public road network in Budapest, Hungary is studied as a graph: Dijkstra’s algorithm is applied to find the shortest path, and the Boykov-Kolmogorov method is used to calculate the maximum flow of the network. Those elements are identified whose damage can critically influence the operation of the network, and where the infrastructure available for rescue teams has a bottleneck. Finally, the Wilcoxon post hoc test was applied with Bonferroni correction. The tests have proven that the new method can successfully identify the critical vulnerabilities of the network to determine its weak points by considering reduced road capacities and the increased needs for transportation arising due to a disaster. This pilot study confirmed that after the elimination of the problems in statistical methods, the new framework can robustly identify those road network elements whose development is of key importance from a disaster management perspective.

How One Instructor Can Teach a Large-Scale, Mastery-Based College Algebra Course Online

ABSTRACT Mastery-based testing is an assessment scheme that encourages students to learn from their mistakes and develop an understanding of material before moving on. For an entry-level course with large enrollment like College Algebra, this could allow some students to move at an appropriate pace for themselves. This paper outlines the changes made to make College Algebra at the University of Florida an asynchronous mastery-based course for the 500+ students who take the course per year and concludes with a series of lessons learned from the endeavor.

A pilot PT scheme for external assessment of laboratory performance in testing synthetic opioid compounds in urine, plasma, and whole blood

A proficiency testing (PT) scheme was prepared for laboratories engaged in bioanalytical testing for synthetic opioid compounds in urine, plasma, and whole blood. Samples were prepared using compounds included in the Opioid Certified Reference Material Kit (Opioid CRM Kit) developed by the U.S. Centers for Disease Control and Prevention. Laboratories received samples during a 2-year project with each year consisting of two PT events 6 months apart. In the first year (pilot test), participants included 10 public health laboratories throughout the United States. In the second year, the group of laboratories expanded to include clinical and forensic drug testing laboratories, and 12 additional participating labs joined the program. In Year 1, overall detection percentages for the compounds present in the PT samples were 95.5% in Event 1% and 97.2% in Event 2. There were 31 apparent false positives reported in Event 1 and four apparent false positives reported in Event 2. Carryover or contamination in laboratory analytical systems were found to be the most significant causes of the false positive results, and none of the laboratories that reported false positives in Event 1 did so in Event 2. In Year 2, overall detection percentages for the compounds present in the PT samples were 89.5% in Event 3% and 94.8% in Event 4. There was one apparent false positive reported in Event 3 and three apparent false positives reported in Event 4. Improvements in drug detection between the two PT events in each year demonstrated the benefit of PT schemes in identifying and addressing potential deficiencies in laboratory systems.

Power System Stability Estimation Scheme Based on Big Data

Aiming at the poor convergence of power flow calculation and the difficulty in location of the power system operation, this paper proposes a fast parallel calculation scheme for power system stability assessment based on big data technology. Through the analysis and research of Newton method which is sensitive to the initial value selection in the actual calculation of regional power flow, an approach for selecting the optimal initial value is proposed by genetic algorithm. Then, by the state sampling method and Monte Carlo parallel simulation, the coarse granularity algorithm under the message passing programming model is designed. The experimental analysis adopts the improved method to test the data in IEEE 9 system, actual environment, the automatic power flow adjustment. The results show that our scheme can achieve high parallel efficiency and acceleration ratio, which improves the calculation ability and accuracy of power flow and reliability evaluation of large-scale power systems.

Determination of seven monoaromatic hydrocarbon metabolites by ultra performance liquid chromatography-tandem mass spectrometry

Monoaromatic hydrocarbons (MAHs) such as benzene, toluene, and xylene are important anthropogenic pollutants in the urban atmosphere. The detection of urinary MAH metabolites are included in human biomonitoring programs in several countries, including Canada, the United States, Italy, and Germany, because their evaluation is vital to monitor the exposure of humans to MAHs. To this end, herein, a method was developed for the determination of seven MAH metabolites through ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). An aliquot of 0.5 mL urine was fortified with an isotopic labeled internal standard solution before being hydrolyzed by 40 μL of 6 mol/L HCl solution, followed by extraction using a 96-well EVOLUTE®EXPRESS ABN solid-phase extraction plate. The samples were washed with 1.0 mL of methanol-water (10∶90, v/v) and eluted with 1.0 mL methanol. The eluate was diluted four times with water prior to use in instrumental analysis. Chromatographic separation was achieved using an ACQUITY UPLC HSS T3 column (100 mm×2.1 mm, 1.8 μm), with gradient elution using 0.1% formic acid as mobile phase A and methanol as mobile phase B. The detection of seven analytes was performed using a triple-quadrupole mass spectrometer equipped with a negative electrospray ionization source in the multiple reaction monitoring mode. The linear ranges of the seven analytes varied from 0.1-20 μg/L to 2.5-500 mg/L, with correlation coefficients greater than 0.995. The method detection limits were 1.5, 0.02, 0.1, 900, 0.6, and 4 μg/L for trans,trans-muconic acid (MU), S-phenylmercapturic acid (PMA), S-benzylmercapturic acid (BMA), hippuric acid (HA), 2-methyl hippuric acid (2MHA), and 3-methyl hippuric acid (3MHA)+4-methyl hippuric acid (4MHA), respectively. The limits of quantification were 5, 0.05, 0.4, 3000, 2, and 12 μg/L for MU, PMA, BMA, HA, 2MHA, and 3MHA+4MHA, respectively. The method was verified by spiking urine samples at three different concentration levels, with recovery rates ranging from 84% to 123%. The intra- and inter-day precisions were 1.8%-8.6% and 1.9%-21.4%, respectively. The extraction efficiencies were 68%-99%, and the matrix effects ranged from -11% to -87%. The urine samples obtained from the German external quality assessment scheme (round 65) were used to assess the accuracy of this method. Both high and low concentrations of MU, PMA, HA, and methyl hippuric acid were within the tolerance range. All analytes in the urine samples were found to be stable for up to seven days at room temperature (20 ℃, absence of light), with less than 15% change in concentration. Analytes in urine samples were found to be stable for at least 42 d at 4 ℃ and -20 ℃, or for six freeze-thaw cycles and up to 72 h in an autosampler (8 ℃). The method was applied to the analysis of 16 non-smokers' and 16 smokers' urine samples. The detection rates of MU, BMA, HA, and 2MHA were 100% in both non-smokers' and smokers' urine samples. PMA was detected in 75% non-smokers' and 100% smokers' urine samples. 3MHA+4MHA was detected in 81% non-smokers' urine and in all smokers' urine samples. Statistical differences were found for MU, PMA, 2MHA, and 3MHA+4MHA between the two groups (p<0.001). The established method has good robustness and can provide reliable results. The experiments were carried out in a high-throughput manner with large sample sizes, owing to the small sample volume, and allowed the successful detection of the seven MAH metabolites in human urine.

Effects of portfolio-based assessment on EFL students’ conceptions and approaches to writing

Researches in general education as well as in language teaching have clearly shown the pivotal role conceptions of learning played on students’ learning outcome. However, there are paucity of researches on instructional and assessment schemes that promote deep conceptions of writing. The main objective of this study, therefore, was to examine the effects of Portfolio-Based Assessment (PBA) on EFL students’ conceptions and approaches to writing. To this end, a pretest posttest control group quasi-experimental research design was adopted, and two sections were chosen from first-year Natural Science Stream students at Wollo University, Dessie Campus. From the two groups, totally 60 participants were chosen randomly, and four types of data collection instruments namely; conceptions of writing scale, essay writing tests, interviews and reflection sheets were employed. The quantitative data were analyzed mainly by using one sample t-test and independent samples t-test, and the qualitative data were also analyzed thematically. During the intervention that stayed for 8 weeks, the students in experimental groups were assessed by writing portfolios. The students in controlled group, however, were assessed by using conventional assessment schemes. As the findings revealed, significant changes in students’ conceptions of writing and writing performances were observed between participants in experimental and controlled groups. The findings suggest that PBA influences EFL students’ deep and meaningful conceptions of writing by way of supporting their independent and out-of class learning endeavor. Moreover, the findings hold implications for using PBA to boost EFL students’ writing self-efficacy beliefs and concern for reflection and revision.

On-the-fly machine learning potential accelerated accurate prediction of lattice thermal conductivity of metastable silicon crystals

In this paper, we propose a convenient strategy to accelerate the evaluation of lattice thermal conductivity through combining phonon Boltzmann transport equation (PBTE) and on-the-fly machine learning potential (FMLP). The thermal conductivity of diamond silicon ($d\text{\ensuremath{-}}\mathrm{Si}$) is evaluated firstly by density functional theory (DFT), FMLP, and empirical potential with PBTE, respectively. The results demonstrate the proposed strategy integrates the prediction accuracy of DFT and computational speed of empirical potential, breaking the dilemma of traditional thermal conductivity assessment schemes. Based on this, the efficient strategy is applied to predict thermal conductivity of 102 low-energy metastable silicon crystals with energies between $d\text{\ensuremath{-}}\mathrm{Si}$ and experimentally ${\mathrm{Si}}_{24}$. Among them, the $Cmcm\text{\ensuremath{-}}{\mathrm{Si}}_{16}, P6/mmm\text{\ensuremath{-}}{\mathrm{Si}}_{36}$-2, $Pnma\text{\ensuremath{-}}{\mathrm{Si}}_{32}$-2 are predicted to host lowest lattice thermal conductivity in $xx$ (8.213 ${\mathrm{Wm}}^{\ensuremath{-}1}{\mathrm{K}}^{\ensuremath{-}1}$), $yy$ (10.917 ${\mathrm{Wm}}^{\ensuremath{-}1}{\mathrm{K}}^{\ensuremath{-}1}$), and $zz$ (11.807 ${\mathrm{Wm}}^{\ensuremath{-}1}{\mathrm{K}}^{\ensuremath{-}1}$) directions, respectively. Such low lattice thermal conductivity benefits from the combined effect of low phonon group velocity and intense phonon scattering caused by distorted $s{p}^{3}$ hybrid states in these metastable silicon crystals. The findings presented in this work provide new candidates and insights of silicon-based materials with ultra-low thermal conductivity, which will greatly expand the applications in thermoelectric and thermal insulation fields.

Evaluation of the Smart Readiness Indicator for Educational Buildings

The Smart Readiness Indicator (SRI) is an assessment scheme for the intelligence of buildings, which was introduced by the European Commission in the directive for the Energy Performance of Buildings in 2018. Since its introduction, many activities related to the maturation and employment of the SRI have been initiated. One of the adaptation needs of the SRI, revealed through public consultation with relevant stakeholders, is the requirement for a tailored SRI for different types of buildings. The aim of this study is to analyze possible scenarios to optimize the smartness performance, as addressed by the SRI score, in educational buildings. The subject of this study concerned campus buildings of the Kaunas University of Technology, in Lithuania. For the definition of the SRI, the calculation sheet developed by the European Commission was used. The effect of the improvements in the smartness performance of buildings on their energy efficiency was examined with the use of a whole-building, BIM-based energy assessment tool (IDA-ICE). The findings of this study revealed that despite the improvement in the automation and control levels of the building heating system, the maximum SRI values achieved deviate significantly by a high-smartness level. This study revealed the importance of services at a city level towards achieving the optimal smartness levels at a building unit level. It also delivered useful findings related to the linkage between energy and smartness performance of a building. The policy implication of the study findings also covers topics relevant to utilities management at a district level, as well as on the need for tailored SRI services catalogs for different types of buildings.

A comprehensive data-driven assessment scheme for power battery of large-scale electric vehicles in cloud platform

In cloud platform with power battery data from large-scale electric vehicles (EVs), cloud battery management system needs to achieve various monitoring tasks, including safety, degradation, and variation analysis. The unstable data quality and deployment conditions limit the full usage of existing methods, such as model-based estimation method and machine learning algorithm. This paper presents a comprehensive data-driven assessment scheme, named as ComDAS, to improve the multi-tasks realization for cloud platform. The proposed ComDAS can be fast deployed for lithium-ion batteries of EVs, and integrates three mainly concerned aspects: capacity estimation, anomaly detection, and variation evaluation. Neural network is applied for calibration of capacity estimation to achieve higher accuracy. A risk scoring method is proposed to achieve long-scale statistics filtering in time dimension, and weeks-early risk pre-warning for anomaly detection. Considering weak labels or even no labels of cloud EV data, correlation analysis among capacity, anomaly, and variation are also calculated to conduct cross validations and reveal the coupling evolution mechanism among the three aspects. Based on the designed monitoring process for large-scale EVs, ComDAS has been deployed to a realistic cloud big-data platform in Sichuan, China. The working ComDAS can hold the capacity error within 4.5 %, obtain the risk pre-warning more than one week earlier, and maintain the variation score of all EVs into 0–100 for further detection. Hence, it proves that ComDAS can maintain satisfying real-time performance for both large-scale EV statistics and specific detection of risky EV.

Hydrogeological conditions of Irpin and their influence on the city’s engineering protection and construction assessment

The scheme of engineering-construction assessment, which is created based on engineering geological zoning of the city’s territory is desirable among additional graphic materials in the design of master plans projects as determined by state building norms [State…, 2012]. Engineering geological zoning provides for different ranks’ selection of taxonomic engineering-geological (EG) units, which have a particular range of common engineering geological conditions that ultimately determine the construction sites’ affiliation to a specific suitability category. Geological-lithological structure and hydrogeological conditions of the Irpin city, Kyiv region are investigated, and the types and degrees ofgroundwater aggressiveness, chemical composition, and mineralization of groundwater, the depths of the first aquifers from the day surface are highlighted in this article. A variant of the creation of large-scale maps of groundwater depth and chemistry based on a hydrogeological survey conducting is presented. The analysis of hydrogeological circumstances of the city’s territory lays the foundations for the selection of engineering-geological sites based on the comparison of this information with geomorphological, engineering-geological and geodynamic data. Complexity assessment of hydrogeological conditions and accounting of hydrogeological factors for the construction assessment scheme and selection of corresponding measures of engineering training and protection of the problem construction sites has become an ultimate result.

Pesticide residues in nectar and pollen of melon crops: Risk to pollinators and effects of a specific pesticide mixture on Bombus terrestris (Hymenoptera: Apidae) micro-colonies

Residues detected in pollen collected by honey bees are often used to estimate pesticide exposure in ecotoxicological studies. However, for a more accurate assessment of pesticides effect on foraging pollinators, residues found directly on flowers are a more realistic exposure approximation. We conducted a multi-residue analysis of pesticides on pollen and nectar of melon flowers collected from five fields. The cumulative chronic oral exposure Risk Index (RI) was calculated for Apis mellifera, Bombus terrestris and Osmia bicornis to multiple pesticides. However, this index could underestimate the risk since sublethal or synergistic effects are not considered. Therefore, a mixture containing three of the most frequently detected pesticides in our study was tested for synergistic impact on B. terrestris micro-colonies through a chronic oral toxicity test. According to the result, pollen and nectar samples contained numerous pesticide residues, including nine insecticides, nine fungicides, and one herbicide. Eleven of those were not applied by farmers during the crop season, revealing that melon agroecosystems may be pesticide contaminated environments. The primary contributor to the chronic RI was imidacloprid and O. bircornis is at greatest risk for lethality resulting from chronic oral exposure at these sites. In the bumblebee micro-colony bioassay, dietary exposure to acetamiprid, chlorpyrifos and oxamyl at residue level concentration, showed no effects on worker mortality, drone production or drone size and no synergies were detected when pesticide mixtures were evaluated. In conclusion, our findings have significant implications for improving pesticide risk assessment schemes to guarantee pollinator conservation. In particular, bee pesticide risk assessment should not be limited to acute exposure effects to isolated active ingredients in honey bees. Instead, risk assessments should consider the long-term pesticide exposure effects in both pollen and nectar on a range of bees that reflect the diversity of natural ecosystems and the synergistic potential among pesticide formulations.

Quality management of the newborn screening network: the Chinese experience.

Quality management of the newborn screening network: the Chinese experience.

A Multibranch U-Shaped Tunable Encoding Chipless RFID Strain Sensor for IoT Sensing System

Structural health monitoring (SHM) is essential for modern large buildings and infrastructure. Radio frequency identification (RFID) widen a new paradigm for SHM in the Internet of Things (IoT) era. This article introduces a low-cost intelligent RFID monitoring system for future IoT applications. Through adding a multiparameter sensing strategy to the passive RFID tags that can be deployed on a large scale to form a sensor network, which expands the coverage of IoT in key positions health monitoring of buildings. In this work, a novel chipless RFID strain sensing tag is designed to characterize the magnitude and direction of metal surface strain, and a low-cost detection method suitable for large mechanical structures is proposed. The traditional strain antennas focus on identifying the strain characteristics without the function of encoding, and there are limitations, such as the rigid measurement methods and the expensive measurement instruments. The tag designed in this article integrates both strain sensing and encoding functions, and has the advantages of small size, high data capacity, and information reading is not easily affected by environmental noise. This article proposes an economical and flexible tag spectrum extraction method, which realizes the intelligent collection and transmission of tag data by connecting lightweight vector network analyzer (VNA) with microcontroller. Combined with the IoT, this method can be well applied to the security assessment and damage detection of large infrastructure structures, which provides a new approach to modern building health monitoring applications from integrated tag design to intelligent detection and risk assessment schemes.

One Health surveillance-A cross-sectoral detection, characterization, and notification of foodborne pathogens.

Several Proficiency Test (PT) or External Quality Assessment (EQA) schemes are currently available for assessing the ability of laboratories to detect and characterize enteropathogenic bacteria, but they are usually targeting one sector, covering either public health, food safety or animal health. In addition to sector-specific PTs/EQAs for detection, cross-sectoral panels would be useful for assessment of the capacity to detect and characterize foodborne pathogens in a One Health (OH) perspective and further improving food safety and interpretation of cross-sectoral surveillance data. The aims of the study were to assess the cross-sectoral capability of European public health, animal health and food safety laboratories to detect, characterize and notify findings of the foodborne pathogens Campylobacter spp., Salmonella spp. and Yersinia enterocolitica, and to develop recommendations for future cross-sectoral PTs and EQAs within OH. The PT/EQA scheme developed within this study consisted of a test panel of five samples, designed to represent a theoretical outbreak scenario. A total of 15 laboratories from animal health, public health and food safety sectors were enrolled in eight countries: Denmark, France, Italy, the Netherlands, Poland, Spain, Sweden, and the United Kingdom. The laboratories analyzed the samples according to the methods used in the laboratory and reported the target organisms at species level, and if applicable, serovar for Salmonella and bioserotype for Yersinia. All 15 laboratories analyzed the samples for Salmonella, 13 for Campylobacter and 11 for Yersinia. Analytical errors were predominately false negative results. One sample (S. Stockholm and Y. enterocolitica O:3/BT4) with lower concentrations of target organisms was especially challenging, resulting in six out of seven false negative results. These findings were associated with laboratories using smaller sample sizes and not using enrichment methods. Detection of Salmonella was most commonly mandatory to notify within the three sectors in the eight countries participating in the pilot whereas findings of Campylobacter and Y. enterocolitica were notifiable from human samples, but less commonly from animal and food samples. The results of the pilot PT/EQA conducted in this study confirmed the possibility to apply a cross-sectoral approach for assessment of the joint OH capacity to detect and characterize foodborne pathogens.

Consistent seismic hazard and fragility analysis considering combined capacity-demand uncertainties via probability density evolution method

A consistent seismic hazard and fragility framework considering combined capacity-demand uncertainties is proposed, in light of the probability density evolution method (PDEM). The PDEM has solid theoretical basis in the reliability field, and it is integrated within the performance-based earthquake engineering (PBEE) for hazard-fragility assessment in this paper. During the analysis, the sample sets with different assigned probability are required to determine in advance, and the equivalent extreme events with virtual stochastic process are required to establish for solution. Both the uncertainties of capacity and demand are considered, and a combined performance index (CPI) is defined as concerned physical variable in PDEM, through pushover static and timehistory dynamic analyses. A non-stationary stochastic earthquake model is introduced using spectral representation of random functions, and the real characteristics of ground motions are reflected by one or two variables for each probability space. The peak ground acceleration (PGA) and spectral acceleration of the first period [Sa(T1)] of non-stationary stochastic ground motions are then obtained for each earthquake level, and the equivalent extreme events are also performed to discuss the statistical information of PGA or Sa(T1) through PDEM. The exceeding probability of PGA or Sa(T1) for each earthquake level is acquired, and a connection between the fragility value and hazard extent is built. The final 3D consistent hazard-fragility curves are then given, and the exceeding probability for different limit states, earthquake levels as well as intensity exceeding conditions can be predicted. Moreover, a comparison with the four classic approaches in the state-of-the-art is performed to verify the accuracy of PDEM procedure. In general, the framework avoids the pre-defined lognormal fragility shape and proves the combined efficiency and accuracy with the Monte Carlo simulation (MCS). The consistency from probabilistic hazard to fragility is realized without re-selecting earthquake waves, which is mainly attributed to the application of PDEM and non-stationary ground motions. The proposed framework provides new ideas for the consistent non-parametric hazard and fragility assessment scheme in the PBEE.

Selection of the Most Appropriate Sustainable Buildings Assessment Categories and Criteria for Developing Countries: Case of Ethiopia

Sustainable buildings can save 36% of total energy use, 65% of electricity consumption, 30% of greenhouse gas emissions, 30% of raw materials use, 30% of waste output, and 12% of potable water consumption. Several sustainable building assessment tools were used by both developed and developing countries. However, Ethiopia’s buildings were not critically assessed and evaluated from a sustainability point of view because there was no such type of study conducted so far. This paper aims to explore the most significant and widely used tools as well as the basis for other sustainable building assessment tools, such as Building Research Establishment Environmental Assessment Methodology (BREEAM), Leadership in Energy and Environmental Design (LEED), Comprehensive Assessment System for Built Environment Efficiency (CASBEE), Sustainable Building Tool (SBTool), Comprehensive Environmental Performance Assessment Scheme (CEPAS), Deutsche Gesellschaft für Nachhaltiges Bauen (DGNB), and Green Mark and Green Star. The methodology employed is the selection of the 10 most commonly and widely utilized sustainable building assessment tools (SBATs) from the 57 SBATs based on desk review and document analysis. The results of the study identified that all 10 SBATs have their own assessment categories and criteria based on many factors, such as climatic conditions and availability of resources, plus methods employing demographic dynamics and legal aspects of the sector for assessing the sustainable/green buildings. It distinguishes the most commonly and repeatedly used assessment categories and criteria and uses a consensus-based approach with experts in the building sectors, a four-quadrant model, and a circular and helical flow model, to develop a new sustainable building assessment tool suitable for Ethiopia.

An alternative risk assessment framework for tropical soil multi-metal contamination using arbuscular mycorrhizal fungi

Arbuscular mycorrhizal fungi (AMF) are a key group of soil organisms involved in several ecosystem services, but they had not been explored in retrospective ecological risk assessment (ERA) schemes, partially due to a lack of experimental protocols. We aimed to perform a site-specific test to assess the effects of multiple metal contaminated soil (Zn, Cu, Cd, and Pb) on several ecotypes of AMF and evaluate the conceptual fitness of the performed AMF test to include in the TRIAD approach of ERA schemes. The results demonstrated that increasing metal contaminated soil proportions that inhibited 50 % (IC50) of spore germination varied from 28 to >80. Ecotypes such as Claroideoglomus etunicatum (IC50 > 80) and Racocetra gregaria (IC50 > 80) experienced 50 % reduction in spore germination at metals concentrations of 10,776.3 for Zn, 1015.2 Cu, 65.5 Cd, 140.2 mg dm−3 Pb, that are 3 times higher than those for Acaulospora mellea CMM101 (IC50 28 [16.2–39.8]) (3441.7 Zn, 333.9 Cu, 17.8 Cd, 56.5 mg dm−3 Pb). In the evaluation of the suitability of the AMF ecotoxicological test to ERA, both spore germination and germinative tube growth were best evaluated and thus suitable in the following descending order: Tier III, Tier II, and Tier I. Variable effects of multiple-metal contamination on the ecotypes indicates how AMF community is affected in its pre-symbiotic structures. The ecotoxicological test allowed the selection of two species with the greatest sensitivity (Ambispora appendicula and Rhizophagus clarus CMM103) to the metal matrix, with the potential to best fit ERA objectives. The site-specific ecotoxicological test with AMF ex-situ proved adequate as an alternative test for Tiers II and III of TRIAD ERA schemes for metal contaminated areas. Data generated through test results, such as the inhibition concentrations (ICs), could be incorporated into ERAs risk indexes, increasing its ecological relevance, and reducing overall uncertainties.

An external quality assessment feasibility study; cross laboratory comparison of haemagglutination inhibition assay and microneutralization assay performance for seasonal influenza serology testing: A FLUCOP study.

External Quality Assessment (EQA) schemes are designed to provide a snapshot of laboratory proficiency, identifying issues and providing feedback to improve laboratory performance and inter-laboratory agreement in testing. Currently there are no international EQA schemes for seasonal influenza serology testing. Here we present a feasibility study for conducting an EQA scheme for influenza serology methods. We invited participant laboratories from industry, contract research organizations (CROs), academia and public health institutions who regularly conduct hemagglutination inhibition (HAI) and microneutralization (MN) assays and have an interest in serology standardization. In total 16 laboratories returned data including 19 data sets for HAI assays and 9 data sets for MN assays. Within run analysis demonstrated good laboratory performance for HAI, with intrinsically higher levels of intra-assay variation for MN assays. Between run analysis showed laboratory and strain specific issues, particularly with B strains for HAI, whilst MN testing was consistently good across labs and strains. Inter-laboratory variability was higher for MN assays than HAI, however both assays showed a significant reduction in inter-laboratory variation when a human sera pool is used as a standard for normalization. This study has received positive feedback from participants, highlighting the benefit such an EQA scheme would have on improving laboratory performance, reducing inter laboratory variation and raising awareness of both harmonized protocol use and the benefit of biological standards for seasonal influenza serology testing.

Improving welfare assessment in aquaculture.

While global aquaculture is rapidly expanding, there remains little attention given to the assessment of animal welfare within aquacultural systems. It is crucial that animal welfare concerns are central in the development and implementation of aquaculture as if they are not prioritized early on, it becomes much more difficult to adapt in future. To this end, it is important to ensure the availability of high-quality welfare assessment schemes to evaluate the welfare of animals in aquaculture and promote and maintain high welfare standards. This paper will first discuss some of the current certification and assessment frameworks, highlighting the primary limitations that need to be addressed, before going on to describe the recommendations for a best-practice welfare assessment process for aquaculture; with the hope that these considerations can be taken on board and used to help improve welfare assessment for aquaculture and, ultimately, to ensure animals used in aquaculture have a higher level of welfare. Any aquacultural system should be assessed according to a suitable framework in order to be considered adequate for the welfare of the animals it contains, and thus to maintain social license to operate.