Assessment Scheme Research Articles

Impact of drinking water treatment processes on the residues of plant protection products for consumer and aquatic risk assessment: theoretical and experimental studies.

Pesticides residues can occur in ground and surface waters, and potentially react with chemicals used for water disinfection treatments, such as chlorine. This can lead to the formation of unknown reaction products, which can be more toxic and/or persistent than the active substances themselves, and therefore become a potential risk for human health and environment. Thus, in the framework of the EU Regulation 1107/2009, the identification of these by-products and their potential risk should be assessed. Within the European Food Risk Assessment (EU-FORA) Fellowship Programme, the fellow studied the behaviour of herbicides belonging to the families of imidazolinones and sulfonylureas in waters treated with chlorine disinfectants. Due to their physicochemical properties, these herbicides are susceptible of reaching natural waters. In fact, some of them have been detected in water monitoring programmes. During the experimental part of the present work programme, reactions between the active substances and the most used chlorine disinfecting reactants (hypochlorite and chloramines) were performed. Degradation kinetic parameters such as half-lives and degradation constants were calculated. Results showed that herbicide degradation was both pH and chlorine/chloramines concentration dependent. In order to identify the degradation by-products, high-resolution mass spectrometry experiments were performed, and a possible route of formation of these compounds was proposed. Finally, their risk assessment was carried out by using tox/ecotoxicological properties determined by QSAR methodology and FOCUS modelling for hazard and exposure assessment, respectively. These results will contribute to the definition of a risk assessment scheme for pesticides by-products potentially occurring in drinking water.

A Method for Assessing the Thickness of Cobalt-Rich Crust on Seamounts and Its Application on the Il’ichev Guyot

Seamount cobalt-rich crusts are rich in cobalt resources and are sought after worldwide. Among different affecting parameters, crust thickness is the most important in evaluating cobalt-rich crust resources in seamounts. Generally, there are two challenges to crust thickness evaluation: firstly, due to high operating costs, most geological stations for seamount exploration have sparse sampling distributions so there are insufficient data to estimate the crust thickness distribution; secondly, a single evaluation method has advantages and disadvantages, and it is not feasible to benefit from the advantages only. These methods cannot simultaneously make full use of the sampling data in local areas, providing a more appropriate evaluation of the whole area. As a result, the estimated results cannot fully reflect the thickness distribution. Based on the thickness data of the station survey and topographic data, geostatistical units are divided, and a comprehensive crust thickness assessment scheme is established on the ArcGIS platform. To this end, the adjacent area method is applied to calculate the crust thickness within the influence range of the station. Combined with the station buffer radius and Thiessen polygon method, the crust thickness within 1.5 km of the survey station was estimated. Then the “slope–distance” Kriging interpolation method was used to calculate the crust thickness in the study area, and the crust thickness in the optimal effective radius area was given to compensate for the missing part in the first step. Finally, the geological blocks were divided using the topographic classification method, and the crust thickness of the remaining unassigned regions was estimated using the mathematical expectation method. The proposed method was applied to evaluate the Il’ichev Guyot’s crust thickness and reasonable results were achieved. It was found that the thickness estimation of the area near the station is consistent with the measured values. Since finer topographic data are used in the calculation, the thickness estimation result is more detailed. In this regard, a simple and effective calculation method was established on the ArcMap platform. The mathematical expectation estimation method of the crust thickness, based on the topographic and geomorphological classification from the perspective of the mineralization mechanism, compensates for the drawbacks of the first two methods originating from the lack of data points. The results show that the proposed method is an appropriate scheme to evaluate seamount crust thickness without comprehensive investigation.

Analysis of Off-target Effects and Risk Assessment Leading from Preclinical to Clinical Trials of Gene-edited Therapeutic Products.

Concerns about off-target effects (OTEs) of genomic DNA cleavages by gene-editing enzymes have been raised, especially for OTEs that go undetected due to technical limitations. Since no explicit guidelines have been in place for risk assessment of OTEs, the regulatory authorities' concept of an acceptable evaluation scheme for OTEs in the investigational drug application (IND) has not been clear. Here, we clarify the regulatory expectations by examining reports on OTE evaluations of leading gene-editing products that have achieved IND clearance. We collected and analyzed the gene-editing products that have entered clinical trials by searching on ClinicalTrials.gov and EU-Clinical-Trial-Registries, and related reports for OTE evaluations from Google Scholar, PubMed, and the developers' websites. We found a common two-step verification method used for different products at the preclinical stage. First, numerous potential off-target loci (POLs) are listed with state-of-the-art high-sensitivity detection methods and theoretical screens; Second, these OTEs are checked by amplicon sequencing of the POLs after treatment by enzymes in in vitro models close to clinical use conditions. Only the OTEs that can be detected and verified are addressed in the risk assessment in the translational phase from preclinical to clinical study. Here, we describe a clear scheme for risk assessment of OTEs at the key translational phase, based on the common features in protocols for gene-editing products that were cleared for use in clinical trials. This report will provide a guide for those newly attempting to conduct clinical development in this field.

Combination with Continual Learning Update Scheme for Power System Transient Stability Assessment.

In recent years, the power system transient stability assessment (TSA) based on a data-driven method has been widely studied. However, the topology and modes of operation of power systems may change frequently due to the complex time-varying characteristics of power systems. which makes it difficult for prediction models trained on stationary distributed data to meet the requirements of online applications. When a new working situation scenario causes the prediction model accuracy not to meet the requirements, the model needs to be updated in real-time. With limited storage space, model capacity, and infinite new scenarios to be updated for learning, the model updates must be sustainable and scalable. Therefore, to address this problem, this paper introduces the continual learning Sliced Cramér Preservation (SCP) algorithm to perform update operations on the model. A deep residual shrinkage network (DRSN) is selected as a classifier to construct the TSA model of SCP-DRSN at the same time. With the SCP, the model can be extended and updated just by using the new scenarios data. The updated prediction model not only complements the prediction capability for new scenarios but also retains the prediction ability under old scenarios, which can avoid frequent updates of the model. The test results on a modified New England 10-machine 39-bus system and an IEEE 118-bus system show that the proposed method in this paper can effectively update and extend the prediction model under the condition of using only new scenarios data. The coverage of the updated model for new scenarios is improving.

Methodology, assessment and application of biotope mapping for urban parks in China: A case study on Riverside Park, Yichang

China, like many other countries in the world, has declining biodiversity caused by urbanization. Urban parks are a patchwork of distinct biotopes and have significant conservation value for biodiversity. Biotope mapping is an essential tool for urban biodiversity conservation, ecological spatial planning and ecosystem management, however there are few studies on it in China. This study explores a practical scheme of biotope classification, assessment and application for urban parks. The classification scheme which integrated vegetation structure was updated to make it clearer and more appropriate for urban parks in factor selection and grade. To identify problems in the biotope, the assessment tool assessed biotope fragmentation and spontaneous vegetation diversity. The number of patches (NP), mean patch size (MPS) and fragmentation index (FI) were used to measure biotope fragmentation, and for species level the richness index and the Jaccard index were selected. These methods were applied to Riverside Park, Yichang as a case study site to verify the applicability and explore methods for biodiversity conservation and restoration based on biotope mapping. The results show that this classification scheme has the potential to become a standard system for urban parks in China, according to the advantages of recognition of human activities and other species, and easy learning. It is also shows that the evaluation method integrating fragmentation and diversity is feasible and reliable to identify the problems of biotope types, and practical strategies are developed according to the assessment results. Our findings provide guidance and reference for professionals on a new method to take urban biodiversity conservation and restoration from research to practice.

Positive Welfare Indicators in Dairy Animals

Nowadays, there is growing interest in positive animal welfare not only from the view of scientists but also from that of society. The consumer demands more sustainable livestock production, and animal welfare is an essential part of sustainability, so there is interest in incorporating positive welfare indicators into welfare assessment schemes and legislation. The aim of this review is to cite all the positive welfare indicators that have been proposed for dairy animals in theory or practice. In total, twenty-four indicators were retrieved. The most promising are exploration, access to pasture, comfort and resting, feeding, and behavioral synchronicity. Qualitative behavioral assessment (QBA), social affiliative behaviors, play, maternal care, ear postures, vocalizations, visible eye white, nasal temperature, anticipation, cognitive bias, laterality, and oxytocin have been also studied in dairy ruminants. QBA is the indicator that is most often used for the on-farm welfare assessment. Among all dairy animals, studies have been performed mostly on cattle, followed by sheep and goats, and finally buffaloes. The research on camel welfare is limited. Therefore, there is a need for further research and official assessment protocols for buffaloes and especially camels.

Florix, an index to assess plant species in floodplains for nature conservation – Developed and tested along the river Danube

Natural floodplains are ecosystems with a diverse mosaic of habitats and site conditions, but also highly threatened due to anthropogenic pressures. Plant species occur in all habitat types and can indicate their value for nature conservation. To improve sustainable management of rivers and floodplains, several indices such as the River Ecosystem Service Index (RESI) have been developed. However, there are so far no assessment schemes for the entire range of floodplain plants. The common assessment approaches like biological integrity, achievement rates or threatened species (Red list), applying to other species groups or other ecosystems, are not appropriate in floodplains. Legal obligations and the need to restore floodplains clearly call for an index assessing the ecological value in a reference area which can be combined with a 5-scale assessment in accordance to established assessments like RESI or the Water Framework Directive.Five typical characteristics describing vascular plants’ adaptation to floodplain habitats were identified. These can be derived from published data sets available for all species in Germany. We checked these indicators for multicollinearity and selected three of them: species number, hydrodynamic indicators, nature conservation indicators. Species number highly correlate with habitat indicators and geographic occurrence. For the selected three indicators we determined thresholds to group habitats and their indicator rate to five classes (very low to very high value for nature conservation). These thresholds are valid for the river Danube and for the habitat types scrutinized in this study.The Florix approach was sensitive in data sets testing active against former floodplains and protected against unprotected areas: For the entire reference region ‘Danube floodplain’, Florix values were higher in the active floodplain and in the protected areas. Only the habitat type ‘water bodies’ showed better scores for habitats in the former floodplain, for ‘softwood forests’ the status of being part of a protected area had no effect. Florix results were validated in two case studies differing in land use intensity. The region with dominant agricultural use showed significantly lower values than that with a higher portion of forests and grasslands.Florix can be used for a floristic conservation status assessment at single habitat level or for the entity of a study region in comparison to a reference region. It allows to identify main pressures and to complement a habitat-type based evaluation. To achieve higher comparability, we should strive for a generalized monitoring in Europe like it is common in aquatic ecosystem monitoring.

A comparison of online and live training of livestock farmers for an on-farm self-assessment of animal welfare

One approach to strengthening the involvement of farmers or stockpersons in the evaluation and improvement of animal welfare is the implementation of an on-farm self-assessment. A valid comparison of the results with reference values, between or within farms, requires that training of the farmers and reliability testing have taken place. We investigated two different training methods (online vs. live) with a total of 146 livestock farmers from farms with dairy cows and calves, beef cattle, sows and suckling piglets, weaners and fattening pigs, laying hens, broiler chickens, and turkeys from all over Germany. Online tests were conducted by assessing photos/videos of each indicator of the assessment scheme to estimate the inter-rater reliability (prevalence-adjusted and bias-adjusted kappa, PABAK). The farmers were requested to provide information on their professional background and rate their motivation to participate in the training and their subjective training success, meaning their confidence in assessing each indicator later on-farm. They evaluated the feasibility of the training and its impact on their views and attitudes. In general, farmers achieved at least substantial inter-rater reliability (PABAK ≥ 0.61) in 86.8% of all initial tests; 13.4% of the tests were repeated once or more times, resulting in a significant improvement of the agreement, with 90.9% of the tests reaching a PABAK ≥ 0.61. However, reliability was higher for indicators with a lower number of score levels. The subjective evaluation of training success was, on average, positive (score = 74.8 out of 100). No effects of the training method or the farmers’ professional background on the inter-rater reliability or the subjective training success were detected. Furthermore, for both methods, farmers moderately agreed that the training had sharpened their views on the animals, encouraged them to implement the assessment on their farm, and made it clear that self-assessment supports animal management. Although the reported costs and time investment for the online training were significantly lower, the effort required for both methods and the ease of integration into the workflow were ranked as similarly acceptable. Overall, both training methods appear feasible for the training of farmers/stockpersons on the assessment of animal-based indicators.

External quality assessment (EQA) for tumor mutational burden: results of an international IQN path feasibility pilot scheme

Tumor mutational burden (TMB) has recently been approved as an agnostic biomarker for immune checkpoint inhibitors. However, methods for TMB testing have not yet been standardized. The International Quality Network for Pathology (IQNPath) organized a pilot external quality assessment (EQA) scheme for TMB testing. The aim of this program was the validation of the materials and the procedures for the EQA of this complex biomarker. Five formalin-fixed paraffin-embedded (FFPE) cell lines were selected to mimic the various TMB values observed in clinical practice. The FFPE samples were tested with the FoundationOne CDx (F1CDx) assay as the reference test and three commercially available targeted sequencing panels. Following this internal validation, the five cell lines were sent to 29 laboratories selected on the basis of a previous survey. Nineteen of the 23 laboratories that submitted results (82.6%) used targeted sequencing for TMB estimation. Only two laboratories performed whole exome sequencing (WES) and two assessed TMB by clinical exome. A high variability in the reported TMB values was observed. The variability was higher for samples with the highest TMB value according to the F1CDx test. However, good reproducibility of the TMB score was shown by laboratories using the same panel. The majority of laboratories did not indicate a TMB cut-off value for clinical interpretation. In conclusion, this pilot EQA scheme suggests that it is feasible to run such an EQA program for TMB assessment. However, the results of our pilot highlight the numerous challenges for the standardization of this test.

Identifying wild bee visitors of major crops in North America with notes on potential threats from agricultural practices

Considering the critical importance of insect pollination to food security and documented declines in wild bee populations, it is imperative to develop effective conservation and management strategies that promote the health of wild bee communities associated with agroecosystems. Identifying wild bee visitors of crops, including crop-flower visitors and species that nest within cropping areas, may prove critical to this endeavor as optimal conservation strategies may differ among bee species and/or guilds, regions, and cropping systems. Although lists of bee species that are associated with North American crops are scattered throughout the literature, there is a need for a comprehensive compilation of those species by crop, region, and nesting guild. Here, we searched the literature to compile a list of wild bee species associated with 33 major crops in North America and assessed the overlap in bee species communities among crops and regions. Of the 739 crop-associated bee species retrieved, 405 species (54.8%) were ground nesters, and 438 species (59.3%) were identified as crop-flower visitors of at least one crop. Because of their nesting and foraging behavior, we argue that these species are more likely to be exposed to agricultural pesticide residues than bee species that do not nest in the ground or feed directly on crop flowers. We further compiled lists of wild bees that have been found to be associated with all of the four most surveyed perennial fruit crops (apple, blueberry, cranberry, strawberry) and all of the three most surveyed cucurbit crops (cucumber, Cucurbita, watermelon) in eastern North America. These lists of bee species can be used to focus attention on species needing better protection strategies within agroecosystems, especially for these two important North American crop groups and can also inform the development of multi-species pesticide risk assessment schemes.

Pesticide soil microbial toxicity: setting the scene for a new pesticide risk assessment for soil microorganisms (IUPAC Technical Report)

Abstract Pesticides constitute an integral part of modern agriculture. However, there are still concerns about their effects on non-target organisms. To address this the European Commission has imposed a stringent regulatory scheme for new pesticide compounds. Assessment of the aquatic toxicity of pesticides is based on a range of advanced tests. This does not apply to terrestrial ecosystems, where the toxicity of pesticides on soil microorganisms, is based on an outdated and crude test (N mineralization). This regulatory gap is reinforced by the recent methodological and standardization advances in soil microbial ecology. The inclusion of such standardized tools in a revised risk assessment scheme will enable the accurate estimation of the toxicity of pesticides on soil microorganisms and on associated ecosystem services. In this review we (i) summarize recent work in the assessment of the soil microbial toxicity of pesticides and point to ammonia-oxidizing microorganisms (AOM) and arbuscular mycorrhizal fungi (AMF) as most relevant bioindicator groups (ii) identify limitations in the experimental approaches used and propose mitigation solutions, (iii) identify scientific gaps and (iv) propose a new risk assessment procedure to assess the effects of pesticides on soil microorganisms.

Behavioral phenotyping of young Scn1a haploinsufficient mice

Dravet syndrome is a rare, severe, infancy-onset epileptic encephalopathy associated with a high premature mortality. In most patients, Dravet syndrome is caused by a heterozygous loss-of-function mutation in the SCN1A gene encoding the alpha 1 subunit of the sodium channel. Of the variety of SCN1A variants identified in patients with Dravet syndrome, SCN1A missense mutations occur in one-third of cases. The novel Scn1a-A1783V mouse model of Dravet syndrome carries the human Ala1783Val missense variant. Recently, the behavioral phenotype of Scn1a-A1783V haploinsufficient adult mice has been characterized, which may provide a valuable basis for assessment of novel therapeutic approaches. However, there is still limited information on the developmental course of behavioral alterations in the Scn1a-A1783V mouse model, which is of particular relevance for conclusions about face validity and severity classification of the model. Based on reference data from young wildtype mice, we analyzed selected behavioral parameters and fecal corticosterone metabolites in the Scn1a-A1783V mouse model during post-weaning development. Differences in the preference for a sweet saccharin solution between Dravet mice and wildtype mice were observed once mice reached sexual maturity. Nest building behavior was already influenced by the Scn1a genotype during prepubescence. Sexually mature Dravet mice showed a significantly reduced burrowing performance as compared to their wildtype littermates. In the open-field test, pronounced hyperactivity and increased thigmotactic behavior were evident in prepubescent and sexually mature Dravet mice. Analysis of Irwin scores revealed several genotype-dependent changes in handling-associated parameters during the course of adolescence. The information obtained provides insight into the age-dependence of behavioral patterns in the novel Scn1a-A1783V mouse model of Dravet syndrome. In addition, the dataset confirms the suitability of the applied behavioral composite measure scheme for evidence-based assessment of cumulative severity in genetic mouse lines.

Nutritional stress exacerbates impact of a novel insecticide on solitary bees' behaviour, reproduction and survival.

Pesticide exposure and food stress are major threats to bees, but their potential synergistic impacts under field-realistic conditions remain poorly understood and are not considered in current pesticide risk assessments. We conducted a semi-field experiment to examine the single and interactive effects of the novel insecticide flupyradifurone (FPF) and nutritional stress on fitness proxies in the solitary bee Osmia bicornis. Individually marked bees were released into flight cages with monocultures of buckwheat, wild mustard or purple tansy, which were assigned to an insecticide treatment (FPF or control) in a crossed design. Nutritional stress, which was high in bees foraging on buckwheat, intermediate on wild mustard and low on purple tansy, modulated the impact of insecticide exposure. Within the first day after application of FPF, mortality of bees feeding on buckwheat was 29 times higher compared with control treatments, while mortality of FPF exposed and control bees was similar in the other two plant species. Moreover, we found negative synergistic impacts of FPF and nutritional stress on offspring production, flight activity, flight duration and flower visitation frequency. These results reveal that environmental policies and risk assessment schemes that ignore interactions among anthropogenic stressors will fail to adequately protect bees and the pollination services they provide.

Unbiased prediction of off-target sites in genome-edited rice using SITE-Seq analysis on a web-based platform.

Genome-editing using the CRISPR-Cas9 system has the potential to substantially accelerate crop breeding. Since off-target editing is one of problems, a reliable method for comprehensively detecting off-target sites is needed. A number of in silico methods based on homology to on-target sequence have been developed, however the prediction without false negative is still under discussion. In this study, we performed a SITE-Seq analysis to predict potential off-target sites. SITE-Seq analysis is a comprehensive method that can detect double-strand breaks in vitro. Furthermore, we developed a systematic method using SITE-Seq in combination with web-based Galaxy system (Galaxy for Cut Site Detection), which can perform reproducible analyses without command line operations. We conducted a SITE-Seq analysis of a rice genome targeted by OsFH15 gRNA-Cas9 as a model, and found 41 candidate off-target sites in the annotated regions. Detailed amplicon-sequencing revealed mutations at one off-target site in actual genome-edited rice. Since this off-target site has an uncommon protospacer adjacent motif, it is difficult to predict using in silico methods alone. Therefore, we propose a novel off-target assessment scheme for genome-edited crops that combines the prediction of off-target candidates by SITE-Seq and in silico programs and the validation of off-target sites by amplicon-sequencing.

Accessibility and visibility of genetic testing for haemophilia across Europe: Where do we stand?

Haemophilia is characterized by bleeding complications resulting from clotting factor VIII (FVIII) or IX (FIX) deficiency. Identifying the causal pathogenic genetic variant denotes a vital aspect of haemophilia management. This study evaluated the accessibility and performances of genetic testing for haemophilia across Europe. The types of genetic analyses, techniques used, turn-around time (TAT) and costs were collected and analysed, as were data updating and quality control. Reported data were retrieved from open access resources, including international databases, Google, laboratory websites, PubMed and government organizations. Overall, 51 genetic laboratories across 15 European countries providing recently updated molecular haemophilia testing were identified. Gene sequencing for small variants of both F8 and F9 genes was provided in most surveyed laboratories. Almost two-thirds of them offer analysis for inversions using a polymerase chain reaction (PCR) method and detection of copy number variation (CNV) using multiplex ligation-dependent probe amplification (MLPA). Cost and TAT were found to vary considerably. In total, 74% of laboratories exhibited a last modified date or change history. The same percentage of laboratories was in possession of an ISO 15189 standard accreditation, whereas only few of them recently performed external quality assessment schemes (EQA) for haemophilia. Despite several initiatives to improve access to genetic testing for haemophilia, such access must still be improved. Our study similarly revealed the large heterogeneity of the variants tested, techniques employed, TAT, cost and quality among the surveyed laboratories.

Comparing diagnostic performance of Cantonese-Chinese version of Rome IV criteria and a short Reference Standard for functional dyspepsia in China

IntroductionFunctional dyspepsia (FD) is diagnosed based on self-reported symptoms and negative upper gastrointestinal endoscopic findings. The Rome criteria were not adopted as a diagnostic instrument in clinical guidelines due to their complexity. Different guidelines used relatively simple symptom assessment schemes with contents that vary significantly. A previously evaluated short Reference Standard may serve as a more standardised tool for guidelines. We evaluated its diagnostic accuracy against the Rome IV criteria in a cross-sectional study in Hong Kong.MethodsA total of 220 dyspeptic patients sampled consecutively from a tertiary hospital and the community completed the Rome IV diagnostic questionnaire, which was translated into Cantonese-Chinese, and the Reference Standard. Sensitivity, specificity, positive and negative likelihood ratios (LRs), and area under the receiver operating characteristics curve (AUC), with 95% confidence intervals (CIs), were calculated.ResultsAmong the participants, 160 (72.7%) fulfilled the Reference Standard with negative upper gastrointestinal endoscopic results. The Reference Standard identified patients with Rome IV-defined FD with 91.1% (95% CI 82.6%–96.4%) sensitivity and 37.6% (95% CI 29.6%–46.1%) specificity. The positive and negative LRs were 1.46 (95% CI 1.26–1.69) and 0.24 (95% CI 0.11–0.49), respectively. The AUC value was 0.64 (95% CI 0.59–0.69).ConclusionsThe Reference Standard can rule out patients without Rome IV-defined FD. It may be used as an initial screening tool for FD in settings where the use of the Rome IV criteria is impractical. It may also provide a uniform definition and diagnostic rule for future updates of clinical guidelines.

Expanding the invasion toolbox: including stable isotope analysis in risk assessment

Species introductions are a major concern for ecosystem functioning, socio-economic wealth, and human well-being. Preventing introductions proved to be the most effective management strategy, and various tools such as species distribution models and risk assessment protocols have been developed or applied to this purpose. These approaches use information on a species to predict its potential invasiveness and impact in the case of its introduction into a new area. At the same time, much biodiversity has been lost due to multiple drivers. Ways to determine the potential for successful reintroductions of once native but now extinct species as well as assisted migrations are yet missing. Stable isotope analyses are commonly used to reconstruct a species’ feeding ecology and trophic interactions within communities. Recently, this method has been used to predict potentially arising trophic interactions in the absence of the target species. Here we propose the implementation of stable isotope analysis as an approach for assessment schemes to increase the accuracy in predicting invader impacts as well as the success of reintroductions and assisted migrations. We review and discuss possibilities and limitations of this methods usage, suggesting promising and useful applications for scientists and managers.

A tree-structure-guided graph convolutional network with contrastive learning for the assessment of parkinsonian hand movements.

Bradykinesia is one of the core motor symptoms of Parkinson's disease (PD). Neurologists typically perform face-to-face bradykinesia assessment in PD patients according to the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). As this human-expert assessment lacks objectivity and consistency, an automated and objective assessment scheme for bradykinesia is critically needed. In this paper, we propose a tree-structure-guided graph convolutional network with contrastive learning scheme to solve the challenge of difficulty in fine-grained feature extraction and insufficient model stability, finally achieving the video-based automated assessment of Parkinsonian hand movements, which represent a vital MDS-UPDRS component for examining upper-limb bradykinesia. Specifically, a tri-directional skeleton tree scheme is proposed to achieve effective fine-grained modeling of spatial hand dependencies. In this scheme, hand skeletons are extracted from videos, and then the spatial structures of these skeletons are constructed through depth-first tree traversal. Afterwards, a tree max-pooling module is employed to establish remote exchange between outer and inner nodes, hierarchically gather the most salient motion features, and hence achieve fine-grained mining. Finally, a group-sparsity-induced momentum contrast is also developed to learn similar motion patterns under different interference through contrastive learning. This can promote stable learning of discriminative spatial-temporal features with invariant motion semantics. Comprehensive experiments on a large clinical video dataset reveal that our method achieves competitive results, and outperforms other sensor-based and RGB-depth methods. The proposed method leads to accurate assessment of PD bradykinesia through videos collected by low-cost consumer cameras of limited capabilities. Hence, our work provides a convenient tool for PD telemedicine applications with modest hardware requirements.

A Multi-Fidelity Approach for Reliability Assessment Based on the Probability of Classification Inconsistency

Abstract Most multi-fidelity schemes for optimization or reliability assessment rely on regression surrogates, such as Gaussian processes. Contrary to these approaches, we propose a classification-based multi-fidelity scheme for reliability assessment. This technique leverages multi-fidelity information to locally construct failure boundaries using support vector machine (SVM) classifiers. SVMs are subsequently used to estimate the probability of failure using Monte Carlo simulations. The use of classification has several advantages: It can handle discontinuous responses and reduce the number of function evaluations in the case of a large number of failure modes. In addition, in the context of multi-fidelity techniques, classification enables the identification of regions where the predictions (e.g., failure or safe) from the various fidelities are identical. At the core of the proposed scheme is an adaptive sampling routine driven by the probability of classification inconsistency between the models. This sampling routine explores sparsely sampled regions of inconsistency between the models of various fidelity to iteratively refine the approximation of the failure domain boundaries. A lookahead scheme, which looks one step into the future without any model evaluations, is used to selectively filter adaptive samples that do not induce substantial changes in the failure domain boundary approximation. The model management strategy is based on a framework that adaptively identifies a neighborhood of no confidence between the models. The proposed scheme is tested on analytical examples of dimensions ranging from 2 to 10, and finally applied to assess the reliability of a miniature shell and tube heat exchanger.

Applying a tiered environmental risk assessment framework to estimate the risk of pesticides to soil organisms in Latin America.

This work investigates the application of a tiered risk assessment scheme for soil organisms based on the risk quotient (RQ) and the toxicity exposure ratio (TER). Forty-five pesticides registered in Latin America were chosen and the ecotoxicological endpoints for earthworms, Collembola, and microorganisms were collated. Tier I assessment was made on conservative assumptions in which no refinements were applied. There, 14 pesticides (31%) exceed the RQ regulatory trigger indicating unacceptable risk, whereas 27 (60%) indicate unacceptable risk on the TER approach. In a Tier II evaluation when refinement options such as foliar interception, field half-life, and the dissipation following the peak estimated environmental concentration are considered, eight (18%) pesticides indicate unacceptable risk based on the RQ, and 15 (33%) indicate unacceptable risk based on the TER. A nonmetric multidimensional scaling evaluation was performed to understand the relevant characteristics involved in how each pesticide poses a risk to soil organisms. Based on the outcome of this analysis, we observed that, for a given pesticide, the combination of high persistence, low or no crop interception, and high toxicity are likely to require higher tier risk assessment. Refinement options can consider either or both the exposure and/or the effect side of the framework. Exposure refinements are potentially simpler and can be conducted with data already available to risk assessors, whereas effect refinements involving further testing with the organisms potentially at risk are still under discussion for intermediate and higher tiers. A sensitive, simple, and logical environmental risk assessment framework can be used to adequately identify risks based on the relevant protection goals that, in turn, will help to protect the desired soil multifunctionality of the ecosystem. We encourage academia and industry to further investigate these topics to provide the most scientifically robust and evidence-based information to decision makers. Integr Environ Assess Manag 2023;19:446-460. © 2022 SETAC.