Journal articles on the topic 'Hierarchical key assignment'

Hierarchical key assignment scheme is an efficient cryptographic method for hierarchical access control, in which the encryption keys of lower classes can be derived by the higher classes. Such a property is an effective way to ensure the access control security of Internet of Things data markets. However, many researchers on this field cannot avoid potential single point of failure in key distribution, and some key assignment schemes are insecure against collusive attack or sibling attack or collaborative attack. In this paper, we propose a hierarchical key assignment scheme based on multilinear map to solve the multigroup access control in Internet of Things data markets. Compared with previous hierarchical key assignment schemes, our scheme can avoid potential single point of failure in key distribution. Also the central authority of our scheme (corresponding to the data owner in IoT data markets) does not need to assign the corresponding encryption keys to each user directly, and users in each class can obtain the encryption key via only a one-round key agreement protocol. We then show that our scheme satisfies the security of key indistinguishability under decisional multilinear Diffie-Hellman assumption. Finally, comparisons show the efficiency of our scheme and indicates that our proposed scheme can not only resist the potential attacks, but also guarantee the forward and backward security.

The time-bound hierarchical key assignment scheme provides a cryptographic solution for the access control problem in distributed systems (e.g., Pay-TV and cloud computing applications). Most time-bound hierarchical key assignment schemes can be divided into two types: adopting tamper-resistant devices and utilizing public values. Despite the fact that adopting tamper-resistant devices can easily resist to collusion attacks, utilizing public values is much cheaper and more suitable for cloud environment. In this paper, we proposed a new time-bound hierarchical key assignment scheme, which can effectively defeat the collusion attack. Besides, the proposed scheme utilizes public values instead of tamper-resistant devices, which will restrict user’s convenience. Compared with the previous works, our scheme requires fewer public values and has better performance.

: For urban rail transit, an environmentally-friendly transportation mode, reasonable passenger flow assignment is the basis of train planning and passenger control, which is conducive to the sustainability of finance, operation and production. With the continuous expansion of the scale of urban rail networks, passenger travel path decision-making tends to be complex, which puts forward higher requirements of networked transportation organization. Based on undirected graphs and the idea of the recursive divide-and-conquer algorithm, this paper proposes a hierarchical effective path search method made up of a three-layer path generation strategy, which consists of deep search line paths, key station paths composed of origin–destination (O-D) nodes and transfer stations, and the station sequence path between the key stations. It can effectively simplify the path search and eliminate obvious unreasonable paths. Comparing the existing research results based on the classical polynomial Logit model, a practical Improved C-Logit multi-path passenger flow assignment model is proposed to calculate the selection ratio of each path in the set of effective paths. Combining the hierarchical path search strategy, the O-D pairs of passenger flow are divided into local-line and cross-line situations. The time-varying cross-line passenger flow is decomposed into a series of passenger sections along the key station paths. A passenger flow pushing assignment algorithm based on line decomposition is designed, which satisfies the dynamic, time-varying and continuous characteristics. The validation of Guangzhou Metro’s actual line network and time-varying O-D passenger demand in 2019 shows that the spatio-temporal distribution results of the passenger pushing assignment have a high degree of coincidence with the actual statistical data.

Abstract: In this work, we employ a key access control management scheme which effortlessly transitions any organization-like security policy to state of the art cloud level security. Offering a very flexible, secure, and hierarchical key access mechanism for institutions that deal with mission-critical data. The scheme also minimizes concerns about moving critical data to the public cloud and ensures only the users with sufficient permission from equal or higher privileged members can access the key by the use of topological ordering of a directed graph which includes self-loop. The main overheads such as public and private storage needs are restricted to a level that is tolerable, and the derivation of key is computationally fast and efficient. From a security perspective, the proposed scheme would be resistant to collaboration attacks and would provide key in distinguishability security. Since the key isn’t stored anywhere so, the problem of a data breach is eliminated. Keywords: Cloud platform; plagiarism check; Shamir’s Secret Key, Cloud security, hierarchical, interpolation, key access, key assignment, secret sharing.

ABSTRACTThe assignment of grammatical functions has been a key feature of hierarchical (serial) models of speech production since their inception in the 1970s. This article argues that grammatical function assignment is neither sufficient nor necessary in such models. It reports a study of the effects of the conceptual accessibility of referents on the selection of English dative syntactic frames in production and shows that the effects relate to linear precedence rather than grammatical function assignment. A secondary topic addressed in the same study is whether second language speakers of English have difficulty integrating syntactic knowledge where it interfaces with conceptual accessibility in speech production. Findings suggest that advanced proficiency speakers do not and are qualitatively similar to native speakers. The implications of this for the interface hypothesis about second language acquisition are discussed.

In today’s increasingly severe network security situation, network security situational awareness provides a more comprehensive and feasible new idea for the inadequacy of various single solutions and is currently a research hotspot in the field of network security. At present, there are still gaps or room for improvement in network security situational awareness in terms of model scheme improvement, comprehensive and integrated consideration, algorithm design optimization, etc. A lot of scientific research investments and results are still needed to improve the form of network security in a long and solid way. In this paper, we propose a network security posture assessment model based on time-varying evidence theory for the existing multisource information fusion technology that lacks consideration of the problem of threat occurrence support rate over time and make the threat information reflect the law of time change by introducing a time parameter in the basic probability assignment value. Thus, the existing hierarchical threat posture quantitative assessment technique is improved and a hierarchical multisource network security threat posture assessment model based on time-varying evidence theory is proposed. Finally, the superiority of the proposed model is verified through experiments.

Gaussian scale mixture models offer a top-down description of signal generation that captures key bottom-up statistical characteristics of filter responses to images. However, the pattern of dependence among the filters for this class of models is prespecified. We propose a novel extension to the gaussian scale mixturemodel that learns the pattern of dependence from observed inputs and thereby induces a hierarchical representation of these inputs. Specifically, we propose that inputs are generated by gaussian variables (modeling local filter structure), multiplied by a mixer variable that is assigned probabilistically to each input from a set of possible mixers. We demonstrate inference of both components of the generative model, for synthesized data and for different classes of natural images, such as a generic ensemble and faces. For natural images, the mixer variable assignments show invariances resembling those of complex cells in visual cortex; the statistics of the gaussian components of the model are in accord with the outputs of divisive normalization models. We also show how our model helps interrelate a wide range of models of image statistics and cortical processing.

This paper established a decomposition hierarchical network model of project level collaborative design process, based on work breakdown structure WBS, for character complex product collaborative design in dynamic alliance. The workflow of product collaborative design was established using time sequence Petri net, and the key assignment which has influence on design schedule and all design time were solved, after analyzing and comparing existing model method of collaborative design. And then experiments were used to verify. Theses technology support time management of workflow in project collaborative and shorten development cycle of collaborative project.

In this study, we have explored and discussed the data mining-based solutions to apparel size assignment using approach principle, K-means clustering, and support vector machine, respectively. A case of mass customization for men's pants in China with 200 adult males were employed to validate and evaluate the solutions. After anthropometric data acquisition and preprocessing, three key body dimensions were identified based on hierarchical clustering, as well as their ranges and fit models. Sequentially, we calculated all the possible values of the distance between the target population and the fit models by the enumeration algorithm. Afterward, we assigned the garment sizes for the target population using the abovementioned data mining approaches. Lastly, the solution based on support machine was considered as the optimal solution for pants mass customization after being comprehensively assessed by the aggregate loss of fit, the number of poor fit, accommodation rate of ideal fit, and the number of garment size employed, since it employed only 48 sizes to reach the accommodation rate of the target population up to 82%. The experimental results demonstrate that the present solution is a low-cost method for size assignment by exploiting the potentials of the existing sizing system, instead of creating new sizing systems, and also easy to be flexibly extended to any types of garments.

SummaryObjectives: Empirical mode decomposition (EMD) is a frequently used signal processing approach which adaptively decomposes a signal into a set of narrow-band components known as intrinsic mode functions (IMFs). For multi-trial, multivariate (multiple simultaneous recordings), and multi-subject analyses the number and signal properties of the IMFs can deviate from each other between trials, channels and subjects. A further processing of IMFs, e.g. a simple ensemble averaging, should determine which IMFs of one signal correspond to IMFs from another signal. When the signal properties have similar characteristics, the IMFs are assigned to each other. This problem is known as correspondence problem.Methods: From the mathematical point of view, in some cases the correspondence problem can be transformed into an assignment problem which can be solved e.g. by the Kuhn-Munkres algorithm (KMA) by which a minimal cost matching can be found. We use the KMA for solving classic assignment problems, i.e. the pairwise correspondence between two sets of IMFs of equal cardinalities, and for pairwise correspondences between two sets of IMFs with different cardinalities representing an unbalanced assignment problem which is a special case of the k-cardinality assignment problem.Results: A KMA-based approach to solve the correspondence problem was tested by using simulated, heart rate variability (HRV), and EEG data. The KMA-based results of HRV decomposition are compared with those obtained from a hierarchical cluster analysis (state-of-the-art). The major difference between the two approaches is that there is a more consistent assignment pattern using KMA. Integrating KMA into complex analysis concepts enables a comprehensive exploitation of the key advantages of the EMD. This can be demonstrated by non-linear analysis of HRV-related IMFs and by an EMD-based cross-frequency coupling analysis of the EEG data.Conclusions: The successful application to HRV and EEG analysis demonstrates that our solutions can be used for automated EMD-based processing concepts for biomedical signals.

Background: Swedish health care organizations (HCOs) are changing using management concepts such as Lean, in attempts of improving efficiency, quality of care and work environment. Since there are pre-conditional challenges for operative managers to engage in change, HCOs tend to assign supportive functions such as change agents (CAs) to facilitate change. Research on the use of CAs in HCOs is sparse, thus the aim of this study explores role assignments and conditions of formally appointed CAs contributing to care process redesign.Methods: A purposive sample of three Swedish hospitals initiating Lean-inspired care process redesign during 2010–2011 was done. In-depth interviews were held with fifty-one key functions during change. Focus group interviews were conducted with thirty-eight health care professionals. Data were analysed by content analysis.Results: Top managers’ goal was to have operative management responsible for change during care process redesign, with support from assigned CAs. Organizing of CAs varied concerning, e.g. their hierarchical positions, job descriptions and practices, and conditions to act as driving forces towards change. Being granted formal power, having earned legitimacy and credibility, clarity regarding roles and responsibilities in change; a good sense of timing and ability to build relationships and trust, were identified as beneficial for CAs to support change.Conclusions: Role assignment and organizing of CAs varies. A position closer to the operative levels, formalized and clarified responsibilities, earned legitimacy and timing support adaptation and alignment of planned change, such as Lean-inspired care process redesign.

Estimation of origin–destination (OD) demand plays a key role in successful transportation studies. In this paper, we consider the estimation of time-varying day-to-day OD flows given data on traffic volumes in a transportation network for a sequence of days. We propose a dynamic linear model (DLM) in order to represent the stochastic evolution of OD flows over time. DLMs are Bayesian state-space models which can capture non-stationarity. We take into account the hierarchical relationships between the distribution of OD flows among routes and the assignment of traffic volumes on links. Route choice probabilities are obtained through a utility model based on past route costs. We propose a Markov chain Monte Carlo algorithm, which integrates Gibbs sampling and a forward filtering backward sampling technique, in order to approximate the joint posterior distribution of mean OD flows and parameters of the route choice model. Our approach can be applied to congested networks and in the case when data are available on only a subset of links. We illustrate the application of our approach through simulated experiments on a test network from the literature.

An aging population and rising life expectancy lead to an increased demand for social services to care for dependent users, among other factors. In Barcelona, home social care (HSC) services are a key agent in meeting this demand. However, demand is not evenly distributed among neighborhoods, and we hypothesized that this can be explained by the user’s social environment. In this work, we describe the user’s environment at a macroscopic level by the socioeconomic features of the neighborhood. This research aimed to gain a deeper understanding of the dependent user’s socioeconomic environment and service needs. We applied descriptive analytics techniques to explore possible patterns linking HSC demand and other features. These methods include principal components analysis (PCA) and hierarchical clustering. The main analysis was made from the obtained boxplots, after these techniques were applied. We found that economic and disability factors, through users’ mean net rent and degree of disability features, are related to the demand for home social care services. This relation is even clearer for the home-based social care services. These findings can be useful to distribute the services among areas by considering more features than the volume of users/population. Moreover, it can become helpful in future steps to develop a management tool to optimize HSC scheduling and staff assignment to improve the cost and quality of service. For future research, we believe that additional and more precise characteristics could provide deeper insights into HSC service demand.

A detailed development of a hierarchical cluster-associate mathematical viscosity model is shown. The model is based on the equilibrium Boltzmann’s distribution and, therefore, is regarded as a chaosensitive property of a fluid inherent in it not only in motion but also at rest. In this model, the key characteristics are chaotic thermal barriers at the melting and boiling points, in connection with which the behavior of a liquid is determined by the action of three energy classes of particles – crystal-mobile, liquid-mobile, and vapor-mobile. An important single indicator in the new model depends on temperature and makes sense of the degree of association of clusters of crystal-mobile particles. The assignment of the activation energy of the viscous flow of melts determined by the Frenkel’s equation to the degree of cluster association gives a constant value commensurate with the binding energy of the van der Waals particle attractive forces. On this basis, the authors hypothesized that a viscous flow occurs due to the destruction of cluster associates while preserving the clusters themselves. To adapt the cluster-associate model to experimental data, certain data processing techniques have been developed to identify unknown model parameters. All calculations are illustrated on liquid lithium and have shown their high adequacy. Also added is a method for processing viscosity data using the entire set of viscosity data while maintaining two reference points and processing the rest to determine the degree of aggregation of associates.

A holistic strategy is established for automated UAV-LiDAR strip adjustment for plantation forests, based on hierarchical density-based clustering analysis of the canopy cover. The method involves three key stages: keypoint extraction, feature similarity and correspondence, and rigid transformation estimation. Initially, the HDBSCAN algorithm is used to cluster the scanned canopy cover, and the keypoints are marked using topological persistence analysis of the individual clusters. Afterward, the feature similarity is calculated by considering the linear and angular relationships between each point and the pointset centroid. The one-to-one feature correspondence is retrieved by solving the assignment problem on the similarity score function using the Kuhn–Munkres algorithm, generating a set of matching pairs. Finally, 3D rigid transformation parameters are determined by permutations over all conceivable pair combinations within the correspondences, whereas the best pair combination is that which yields the maximum count of matched points achieving distance residuals within the specified tolerance. Experimental data covering eighteen subtropical forest plots acquired from the GreenValley and Riegl UAV-LiDAR platforms in two scan modes are used to validate the method. The results are extremely promising for redwood and poplar tree species from both the Velodyne and Riegl UAV-LiDAR datasets. The minimal mean distance residuals of 31 cm and 36 cm are achieved for the coniferous and deciduous plots of the Velodyne data, respectively, whereas their corresponding values are 32 cm and 38 cm for the Riegl plots. Moreover, the method achieves both higher matching percentages and lower mean distance residuals by up to 28% and 14 cm, respectively, compared to the baseline method, except in the case of plots with extremely low tree height. Nevertheless, the mean planimetric distance residual achieved by the proposed method is lower by 13 cm.

3140 Background: Precision oncology is associated with favorable outcomes in selected patients with cancer. Our first IMPACT trial (IMPACT1) demonstrated that in sequential patients with advanced cancer who had tumor molecular testing and participated in phase I clinical trials, matched targeted therapy (MTT) was associated with superior rates of response, progression-free survival (PFS) and overall survival compared with those of patients who received non-MTT. Despite the statistical significance for these outcomes, the study was non-randomized. Recognizing that it would be difficult to randomize patients we nonetheless undertook IMPACT2, a phase 2 randomized study to determine whether patients treated on the basis of tumor genomic alterations have longer PFS compared to those whose treatment is not selected on the basis of molecular alteration analysis. Methods: Patients with metastatic cancer undergo a tumor biopsy and genomic profiling. Patients are presented at tumor board and are offered to be randomized between two arms: MTT or non-MTT, when criteria (biomarker present, available clinical trial, eligibility criteria met, insurance approval) are met. In April 2019, we amended the trial to include a “patient-preference” cohort for each arm. Patients who decline randomization are offered choice of arm (ClinicalTrials.gov: NCT02152254). The primary analysis will use both randomized and patient-preference cohorts based on a Bayesian hierarchical model that “borrows” from the patient-preference cohorts to the extent to which its PFS agrees with that in the randomization cohort. Results: The key barriers randomizing patients with actionable molecular alterations are patient-related (advanced, metastatic setting requiring immediate intervening therapy; decline in performance status, organ function; or death); drug-related (FDA-approved drug available; or unavailable MTT against key driver biomarker) or financial (no insurance coverage of MTT; lack of patient resources to participate in trials). As the study spans over a few years, some investigational agents that were considered non-MTT at the time of treatment assignment were later proven to be MTT (e.g., immunotherapeutic agents targeting high tumor mutational burden); and/or were approved by the FDA. Conclusions: Although randomized trials have been considered the gold standard in drug development, such studies in the advanced metastatic setting are complicated. The benefit of Precision Oncology has been exemplified in individual patients who were treated with biomarker-selected therapy. The adaptive design of IMPACT2 enables patient randomization despite the evolving tumor biomarkers and the plethora of investigational drugs. IMPACT2 provides insights for the development of cancer genome-based medicine. Outcomesfor randomized patients are awaited. Clinical trial information: NCT02152254.

Main text The CCQM-K156 comparison was coordinated by TUBITAK UME on behalf of the Organic Analysis Working Group (OAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) for National Measurement Institutes (NMIs) and Designated Institutes (DIs) which provide measurement services in organic analysis under the 'Comité International des Poids et Mesures' Mutual Recognition Arrangement (CIPM MRA). Perfluoro alkyl substances (PFAS) such as PFOS and PFOA have been used in numerous industrial applications and products. Because of their high stability and resistance to biodegradation, atmospheric photooxidation, direct photolysis and hydrolysis, they are extremely persistent in the environment. The European Union (EU) Water Framework Directive lists PFOS as a priority hazardous substance that poses a significant risk to the aquatic environment. The use of PFOS-containing Aqueous Film-Forming Foams (AFFFs) has been banned since June 2011 in the EU. As relatively water-soluble, effectively non-degradable compounds, PFOS and PFOA migrate to ground water. They are not removed in the conventional drinking water treatment, and therefore cause health risks in polluted areas. The EU Drinking Water Directive and the European Commission has proposed a limit value of 100 ng/L for the sum of 20 PFAS, including PFOS and PFOA. This study provides the means for assessing measurement capabilities for determination of high polarity measurands in a procedure that requires extraction, clean-up, analytical separation and detection. Successful participation in CCQM-K156 demonstrates measurement capabilities in determining mass fraction of organic compounds, with a molecular mass of 200 g/mol to 700 g/mol, having high polarity pKow > -2, in a mass fraction range from 0.5 ng/kg to 500 ng/kg in aqueous media. Nine NMIs and DIs participated in the CCQM-K156 key comparison. Seven institutes reported their results. SPE was applied in the sample pre-treatment and LC-MS was applied for detection. All participating laboratories applied isotope dilution mass spectrometry (IDMS) techniques for quantification. Participants established the metrological traceability of their results using certified reference materials (CRMs) from NMIs with stated traceability; where commercially available high purity materials were used the purity was determined in-house. The CCQM-K156 results for L-PFOA and L-PFOS range from 2.75 ng/kg to 5.50 ng/kg with a % RSD of 19.5 % for L-PFOA and from 2.04 ng/kg to 4.45 ng/kg with a % RSD of 21.3 % for L-PFOS. The KCRV was assigned using a Hierarchical Bayesian Random Effects Model (HB REM) estimator from the values reported by six of the participants. One participant result of L-PFOS and one result of L-PFOA were excluded from the KCRV for technical reasons. The KCRV was 4.9 ng/kg ± 0.4 ng/kg for L-PFOA and 3.8 ng/kg ± 0.4 ng/kg for L-PFOS. The six institutes that were included in the assignment of consensus KCRV all agreed within their standard uncertainties. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/. The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Colorimetric sensor arrays incorporating red, green, and blue (RGB) image analysis use value changes from multiple sensors for the identification and quantification of various analytes. RGB data can be easily obtained using image analysis software such as ImageJ. Subsequent chemometric analysis is becoming a key component of colorimetric array RGB data analysis, though literature contains mainly principal component analysis (PCA) and hierarchical cluster analysis (HCA). Seeking to expand the chemometric methods toolkit for array analysis, we explored the performance of nine chemometric methods were compared for the task of classifying 631 solutions (0.1 to 3 M) of acetic acid, malonic acid, lysine, and ammonia using an eight sensor colorimetric array. PCA and LDA (linear discriminant analysis) were effective for visualizing the dataset. For classification, linear discriminant analysis (LDA), (k nearest neighbors) KNN, (soft independent modelling by class analogy) SIMCA, recursive partitioning and regression trees (RPART), and hit quality index (HQI) were very effective with each method classifying compounds with over 90% correct assignments. Support vector machines (SVM) and partial least squares – discriminant analysis (PLS-DA) struggled with ~85 and 39% correct assignments, respectively. Additional mathematical treatments of the data set, such as incrementally increasing the exponents, did not improve the performance of LDA and KNN. The literature precedence indicates that the most common methods for analyzing colorimetric arrays are PCA, LDA, HCA, and KNN. To our knowledge, this is the first report of comparing and contrasting several more diverse chemometric methods to analyze the same colorimetric array data.

Abstract Abstract 1731 Background: Symptom burden in primary, post-ET and post-PV myelofibrosis (MF) is frequently severe and correlates with a poor prognosis. However, symptom manifestations are heterogeneous with variable presence of specific symptoms, splenomegaly and cytopenias. We sought to identify the spectrum and features of MF symptomatic phenotypes by cluster analysis of prospectively gathered information on MF symptoms and disease features. Methods: Data was collected among an international cohort of subjects with MF. Data included demographics, disease features and completion of the Brief Fatigue Inventory (BFI) and Myeloproliferative Neoplasm Symptom Assessment Form Total Symptom Score (MPN-SAF TSS) (Blood 2011; 118:401–408). Surveyed symptoms addressed key disease features on a 0 (absent) to 10 (worst-imaginable) scale. Cluster development was based on consideration of r-squared in hierarchical clustering using Ward's linkage. Final cluster assignment was based on the nonhierarchical k-means method. Comparisons between symptom clusters were based on ANOVA and chi-squared tests. Results: Subject Demographic and Disease Characteristics: Data from 329 prospectively enrolled persons with MF was collected (Chinese 102, French 54, German 19, Italian 22, Dutch 45, English 51, Spanish 29, Swedish 7) including 223 PMF, 67 post-ET MF and 39 post-PV MF patients. Participants were of typical age (mean 59) and gender (47% F). Among all participants, four natural symptom clusters were identified (Figure 1). Among clusters, disease features including leukopenia, thrombocytopenia, and enlarged spleen varied significantly between clusters (P<0.05). Cluster 1: The “Fatigue Dominant with Few Lab Abnormalities” Profile (n=150 (46%; 69% PMF, 20% post-ET MF, 11% post-PV MF)). Cluster 1, the largest, is characterized by fatigue-dominant complaints in the setting of the lowest overall MPN-SAF TSS and highest proportion of males (59%). Individuals among this group have the lowest prevalence of laboratory abnormalities (65% total; anemia, 67%; thrombocytopenia, 20%) or clinical deficiencies including enlarged spleen (average 6.0 cm below costal margin), prior thrombosis (9%), prior hemorrhage (5%) or prior RBC-transfusions (20.4%). Interestingly, individuals in this group are most likely to have had prior splenectomy (5.8%). Cluster 2: The “Cognitive Complaints with Enlarged Spleen” Cluster (n=105 (32%; 65% PMF, 20% post-ET MF, 15% post-PV MF)). Cluster 2 is the 2nd largest cluster. Subjects have relatively few abnormal lab values (67% vs 65%–77%) but have high severity of fatigue, sexual difficulties, insomnia, inactivity and reduced QOL. These individuals have the largest spleen size (8.7cm below costal margin). Cluster 3: The “Nighttime and Cognitive Complaints” Group (n=53 (16%; 64% PMF, 25% post-ET MF, 11% post-PV MF)). Cluster 3 is the smallest cluster. Subjects have many cognitive and nighttime-related complaints including sexual difficulties, night sweats, insomnia, and concentration problems. Subjects with post-ET MF are predominant. This cluster also has the 2ndsmallest spleen size (7 cm) or history of prior thrombosis (9.6%), hemorrhage (7.8%) or requirement for transfusions (21.2%). Cluster 4: The “Severe Fatigue with Few End-organ Complaints” Cluster (n=21 (6%; 81% PMF, 14% post-ET MF, 5% post-PV MF)). Cluster 4 is the most symptomatic cohort with the highest proportion of subjects with PM. There is a lower frequency of end-organ complaints including abdominal pain, cough, and headaches. Symptoms including sexual difficulties, sad mood and insomnia are predominant. No subjects had prior splenectomy. Subjects also have the highest prevalence of prior thrombosis (29%), hemorrhage (14%), and transfusions (43%). Additionally, this cohort has the largest prevalence of lab abnormalities (77%) with thrombocytopenia (71%), leukopenia (41%) and anemia (41%). Conclusion: This analysis will allow us to examine a new framework for evaluating persons with MF using symptom profiles and is the 1st cluster evaluation of MF. Lab and physical findings contrast significantly between symptom clusters indicating these phenotypic symptoms likely result from etiological factors present in specific disease phenotypes. Future studies should evaluate whether there is a correlation between cluster profiles, prognosis and genotype. Disclosures: Kiladjian: Celgene: Research Funding; Novartis: Honoraria, Research Funding; Shire: Honoraria. Roy:Novartis, BMS: Speakers Bureau. Harrison:Novartis: Honoraria, Research Funding, Speakers Bureau; YM Bioscience: Consultancy, Honoraria; Sanofi Aventis: Honoraria; Shire: Honoraria, Research Funding. Vannucchi:Novartis: Membership on an entity's Board of Directors or advisory committees. Passamonti:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees. Mesa:Incyte: Research Funding; Lilly: Research Funding; Sanofi: Research Funding; NS Pharma: Research Funding; YM Bioscience: Research Funding.

Purpose In the current labour market, the competence to adapt is becoming significantly relevant for career development and career success. The construct of career adaptability, i.e. the capability to adapt to changing career-related circumstances and predict advancement in career development, seems to provide a fruitful scientific base for successful career intervention. The purpose of the study is exploratory, with the aim of providing new findings about the key predictors of this meta-competence that are relevant for career development. Design/methodology/approach Through a web-based survey, a convenience sample of 230 working participants completed an online questionnaire, including socio-demographic characteristics (age, gender, education), professional status (role seniority, sector of employment, professional role), professional development-related features (training, new professional assignments, financial incentives) and psychological factors (work self-efficacy, search for work self-efficacy and job satisfaction). Four-step hierarchical multiple regression analyses were conducted to understand which of these factors account for the most career adaptability variance. Findings Results highlight that work self-efficacy, search for work self-efficacy and education play a significant role in predicting career adaptability. Surprisingly, professional development-related features and professional status do not seem to have a relevant influence. Practical implications Training and career-development professionals can improve their understanding of which career-related skills and attitudes can increase one’s capability to cope with sudden changes and instability of the current labour market. Originality/value This study supports previous research, addressing the importance of career adaptability in times of dramatic change. It also provides some insight into the factors that could predict it.

Background Binding of E-selectin (E-sel) to sialyl Lex, the E-sel ligand, on the leukemic cell surface activates cell survival pathways and promotes chemotherapy resistance in AML. Higher expression of E-sel ligand is associated with relapse and poor survival. Uproleselan (GMI-1271), a novel E-selectin antagonist, disrupts cell survival pathway activation, enhances chemotherapy response and protects from toxicity such as mucositis with improved survival in vivo. Preclinical data support combination of uproleselan with chemotherapy improves response without additional toxicity. A phase 1/2 study (NCT02306291) of uproleselan added to chemotherapy (mitoxantrone, etoposide, cytarabine, MEC) in R/R AML showed promising outcomes at the recommended phase 2 dose (RP2D), including a CR/CRi rate of 41% and median OS of 8.8 m (95% CI 5.7-11.4). 11/16 (69%) evaluable patients were MRD negative (DeAngelo et al ASH 2018). Patients with sufficient expression of the appropriate E-selectin ligand (the target of the E-selectin inhibitor) exhibited higher CR/CRi rate and longer survival. Median OS for Leukemic blasts/E-sel ligand ≥10% vs leukemic blasts/E-sel ligand <10% was 12.7m and 5.2 m, respectively (report in progress). Collectively, these data indicate that high E-sel ligand expression may contribute to clinical chemotherapy resistance, particularly increasing the risk of relapse, which can be reversed with E-sel inhibition. In addition, chemotherapy is well known to cause severe mucositis, with resultant infections, prolongation of hospital stay, morbidity and mortality, and a dramatic reduction in the expected incidence and severity of mucositis was seen with uproleselan in combination with MEC. At the RP2D, Grade 3/4 mucositis was 2%. Breakthrough Therapy Designation was granted by FDA for treatment of patients with R/R AML. A pivotal phase 3 study (NCT03616470) is underway. The aims of this phase 3, double-blind, placebo controlled study are to assess the efficacy and safety of uproleselan with standard salvage chemotherapy in R/R AML, evaluate the incidence of MRD, and assess for correlation of E-sel ligand expression on blasts with outcomes in R/R AML. Study Design and Methods This study is a global, randomized, double-blind, placebo-controlled phase 3 registration trial. Major Eligibility Criteria ≥18 to ≤75 years old Primary refractory AML, first or second relapse of AML Prior transplant (HSCT) is allowed Must be medically eligible for chemotherapy ECOG performance status ≤2 Study treatment and endpoints Treatment is MEC or FAI (fludarabine, cytarabine, idarubicin) induction with blinded study drug (uproleselan/placebo at 1:1 ratio) administered 1 day prior (sentinel dose) and then BID through 2 days post chemotherapy. Consolidation (HiDAC/IDAC) with uproleselan/placebo (same assignment) up to 3 cycles is allowed. The primary endpoint is overall survival; key secondary endpoints include the incidence of severe oral mucositis during induction and CR/CRh rate. Measurable residual disease, event free survival, safety, and pharmacokinetics will also be evaluated. In addition, the relationship between E-sel ligand expression on leukemic cells in the bone marrow and clinical outcomes in AML will be determined. Statistical methods The phase III primary endpoint will compare overall survival between the treatment arms using a stratified log-rank test. Stratification factors will be age group, disease status, backbone chemotherapy and prior transplant status. Median time to event values will be estimated using the Kaplan-Meier method. The study is powered to detect an improvement in median OS using a log-rank test (HR= 0.68, one-sided 0.025 type I error rate). A hierarchical testing procedure will be used to assess the statistical significance of the key secondary analyses, incidence of severe oral mucositis and remission rate (CR/CRh, CR). Study status This trial is expected to enroll 380 patients across approximately 9 countries in North America, Europe, and Australia. The first patient was enrolled in November 2018. Disclosures DeAngelo: Novartis: Consultancy, Patents & Royalties: Royalty, Research Funding; Takeda Pharmaceuticals: Consultancy; Jazz Pharmaceuticals Inc: Consultancy; Incyte: Consultancy; Amgen: Consultancy; Pfizer: Consultancy; Abbvie: Research Funding; GlycoMimetics: Research Funding; Celgene: Consultancy; Blue Print Medicines: Consultancy, Research Funding; Shire: Consultancy. Erba:Agios: Consultancy, Speakers Bureau; Novartis: Consultancy, Research Funding, Speakers Bureau; Daiichi Sankyo: Consultancy, Research Funding; Novartis: Consultancy, Research Funding, Speakers Bureau; MacroGenics: Consultancy, Other: Lecture fees, Research Funding; MacroGenics: Consultancy, Other: Lecture fees, Research Funding; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Seattle Genetics: Consultancy; Seattle Genetics: Consultancy; GlycoMimetics: Consultancy, Other: Chair, data and safety monitoring board, Research Funding; Amgen: Consultancy; Amgen: Consultancy; Pfizer: Consultancy; Pfizer: Consultancy; Celgene: Consultancy, Other: chair, AML Registry Scientific Steering Committee, Speakers Bureau; Celgene: Consultancy, Other: chair, AML Registry Scientific Steering Committee, Speakers Bureau; Daiichi Sankyo: Consultancy, Research Funding; GlycoMimetics: Consultancy, Other: Chair, data and safety monitoring board, Research Funding; Covance: Other: Fees for serving as chair on an independent review board for AbbVie Phase III studies; Covance: Other: Fees for serving as chair on an independent review board for AbbVie Phase III studies; AbbVie: Consultancy, Other: Chair, IRC for phase III studies, Research Funding; AbbVie: Consultancy, Other: Chair, IRC for phase III studies, Research Funding; Agios: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Astellas Pharma: Consultancy; Astellas Pharma: Consultancy; ImmunoGen: Consultancy, Research Funding; ImmunoGen: Consultancy, Research Funding. Jonas:AbbVie, Amgen, Celgene, GlycoMimetics, Jazz, Pharmacyclics, Tolero: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie, Accelerated Medical Diagnostics, AROG, Celgene, Daiichi Sankyo, Esanex, Forma, Genentech/Roche, GlycoMimetics, Incyte, LP Therapeutics, Pharmacyclics: Research Funding; AbbVie, Amgen, GlycoMimetics: Other: Travel expenses. O'Dwyer:AbbVie: Consultancy; GlycoMimetics Inc: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding; Onkimmune: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Research Funding. Marlton:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees. Liesveld:Abbvie: Membership on an entity's Board of Directors or advisory committees; Onconova: Other: Data safety monitoring board. Bhatnagar:Novartis and Astellas: Consultancy, Honoraria; Cell Therapeutics, Inc.: Other: Research support; Karyopharm Therapeutics: Other: Research support. Uy:Astellas: Consultancy; Pfizer: Consultancy; Curis: Consultancy; GlycoMimetics: Consultancy. Cull:Amgen: Other: Travel, accommodation ; AbbVie: Other: Travel, accommodation; Glycomimetics: Other: Travel, accommodation. Armstrong:GlycoMimetics: Consultancy. Fogler:GlycoMimetics Inc: Employment, Equity Ownership. Chen:GlycoMimetics: Employment. Magnani:GlycoMimetics Inc: Employment, Equity Ownership. Thackray:GlycoMimetics Inc: Employment. Feldman:GlycoMimetics Inc: Employment. Advani:Macrogenics: Research Funding; Glycomimetics: Consultancy, Research Funding; Kite Pharmaceuticals: Consultancy; Amgen: Research Funding; Abbvie: Research Funding; Pfizer: Honoraria, Research Funding. Becker:Accordant Health Services/Caremark: Consultancy; AbbVie, Amgen, Bristol-Myers Squibb, Glycomimetics, Invivoscribe, JW Pharmaceuticals, Novartis, Trovagene: Research Funding; The France Foundation: Honoraria.

The scientific discussion concerning the development of the promising approaches for phyto-diversity conservation and the rational use of plant resources in Russian Federation was held at the Presidium of the Russian Academy of Sciences in December 2019. After the reports of leading scientists from biological institutes, a resolution No. 195 dated December 10, 2019 «Global changes in terrestrial ecosystems of Russia in the 21st century: challenges and opportunities» was adopted. The resolution includes a set of priority scientific aims including the development and application of modern technologies for inventory of the plant communities and the development of vegetation classification in Russia. As a result of the opinion exchange between phytocoenologists from different regions, the Concept of Russian Vegetation Classification was proposed. It is based on the following principles. 1. The use of the ecological-floristic approach and the hierarchy of the main syntaxonomic categories applied for the Classification of Vegetation of Europe. 2. Development of the Russian archive of geobotanical relevés and syntaxa in accordance with international standards and with the remote access functions. 3. Application of strict rules for syntaxon names formulated in the International Code of Phytosociological Nomenclature. The Concept assumes the development of a special program «Russian Vegetation Classification» with the justification of the necessity for targeted funding of the program in Research Institutions and Universities involved for solving this scientific problem on the principle of network collaboration. The final results of this program will be represented in the multi-volume publication «Vegetation of Russia». A shortened version of the Concept (English version was kindly revised by Dr. Andrew Gillison, Center for Biodiversity Management, Cairns, Queensand, Australia) is below. Vegetation classification of Russia Research Program Concept Systematic classification and inventory of plant communities (phytocoenoses) is fundamental to the study and forecasting of contemporary complex processes in the biosphere, controlled among other factors, by global climate change. Vegetation classification serves as a common language that enables professionals in various fields of science to communicate and interact with each other in the process of studying and formulating practical ecosystem-related management decisions. Because plant community types can carry a great deal of information about the environment, nearly all approaches to simulation of changes in global biota are based inevitably on vegetation categories. Phytocoenosis is a keystone element when assessing the biodiversity genetic potential, formulating decisions in biological resource management and in sustaining development across Russian territories. Among the world’s vegetation classification systems, phytosociology is a system in which the concept of plant association (basic syntaxon) is the basic element in the classification of phytocoenoses. The phytosociological approach as applied in this concept proposal, has its origins in the Brussels Botanical Congress in 1910. However, despite the broad acceptance of phytocoenotic diversity as a fundamental methodological tool for understanding biosphere processes and managing biological resources nowadays, we still lack a unified approach as to its systematization at both global and country levels with the consequence that, there is no a single classification system. The results obtained by vegetation scientists working under European Vegetation Survey led by L. Mucina became the effective reference for international cooperation in vegetation classification. In the last 17 years they have produced a system of vegetation classification of Europe, including the European part of Russia (Mucina et al., 2016. «Vegetation of Europe: hierarchical floristic classification system of vascular plant, bryophyte, lichen, and algal communities»). Despite the fact that «Vegetation of Europe» is based on ecological and floristic principles, it nevertheless represents an example of the synthesis of one of the most effective approaches to systematizing vegetation diversity by different vegetation science schools. The synthetic approach implemented in this study assumes full accounting of the ecological indicative significance of the floristic composition and structure of plant community and habitat attributes. The approach has already demonstrated its high efficiency for understanding and forecast modeling both natural and anthropogenic processes in the biosphere, as well as in assessment of the environmental and resource significance of vegetation (ref). The demand for this approach is supported by its implementation in a number of pan-European and national projects: NATURE 2000, CORINE, CarHAB, funded at the state and pan-European levels. Currently, one of the main systems for the study and protection of habitats within the framework of environmental programs of the European Union (Davies, Moss, 1999; Rodwell et al., 2002; Moss, 2008; Linking..., 2015; Evans et al., 2018) is EUNIS (European Nature Information System), the framework of which is a multilevel classification of habitats in Europe has been established. EUNIS was used as the basis for the preparation and establishment of the Red List of European Habitats (Rodwell et al., 2013). It is approved by the Commission of the European Union (EU) (Habitats Directive 92/43 / EEC, Commission of the European Communities) for use in environmental activities of EU countries. In its Resolution of 10.12.2019, the Presidium of the Russian Academy of Sciences (RAS) expressed the need in a modern vegetation classification for the assessment of the ecosystem transformations under current climate changes and increasing anthropogenic impacts, as well as in development of effective measures for the conservation and rational use of plant resources of Russia. The resolution recommended the development of the Concept of Vegetation Classification of Russia to the Science Council for biodiversity and biological resources (at RAS Department of biological sciences — Section of Botany). As a consequence, a group of Russian vegetation researchers has developed the Concept for Vegetation Classification of Russia and proposed principles and a plan for its implementation. Aim Elaboration of a system of vegetation classification of Russia reflecting the natural patterns of plant communities formation at different spatial and geographical levels and serving as the fundamental basis for predicting biosphere processes, science-based management of bioresources, conservation of biodiversity and, ultimately, rational nature management for planning sustainable development of its territories. Research goals 1. Development of fundamental principles for the classification of vegetation by synthesis of the achievements of Russian and world’s vegetation science. 2. Inventory of plant community diversity in Russia and their systematization at different hierarchical levels. Elaboration and publication of a Prodromus of vegetation of Russia (syntaxon checklist) with an assessment of the correctness of syntaxa, their Nomenclatural validization and bibliography. Preparation and publication of a book series «Vegetation of Russia» with the entire classification system and comprehensive description of all syntaxonomic units. 3. The study of bioclimatic patterns of the phytocoenotic diversity in Russia for predictive modeling of biosphere processes. Assessment of qualitative changes in plant cover under global climate change and increasing anthropogenic impact in its various forms. 4. Assessment of the conservation value of plant communities and ecosystems. Habitat classification within Russia on the basis of the vegetation classification with a reference to world experience. 5. Demonstration of the opportunities of the vegetation classification for the assessment of actual plant resources, their future prognoses under climate and resource use change, optimization of nature management, environmental engineering and planning of projects for sustainable development. Basic principles underlying the vegetation classification of Russia I. Here we address the synthesis of accumulated theoretical ideas about the patterns of vegetation diversity and the significant features of phytocoenoses. The main goal is to identify the most significant attributes of the plant cover at different hierarchical levels of classification: floristic, structural-phytocoenotic, ecotopic and geographical.We propose the following hierarchy of the main syntaxonomical categories used in the classification of European vegetation (Mucina et al., 2016) by the ecological-floristic approach (Braun-Blanquet): Type of vegetation, Class, Order, Alliance, Association. Applying the ecological-floristic approach to the vegetation classification of Russia will maximize the use of the indicative potential of the plant community species composition to help solve the complex tasks of modern ecology, notably plant resource management, biodiversity conservation, and the forecast of vegetation response to environmental change of environment changes. II. We plan to establish an all-Russian archive of geobotanical relevés in accordance with international standards and reference information system on the syntaxonomical diversity coupled with implemented remote access capabilities. At present, the archives in botanical, biological, environmental and geographical institutes of the Russian Academy of Sciences, as well as those of universities, have accumulated a large mass of geobotanical relevés for most regions of Russia (according to preliminary estimates — more than 300,000). These documents, which are fundamental to solving the most important national tasks for the conservation and monitoring of the natural human environment, need to be declared a National treasure. In this respect, the development of the all-Russian Internet portal for the vegetation classification is an urgent priority. III. The vegetation classification procedure will be based on a generalization of field data (geobotanical relevés) performed in accordance with international standards, using up-to-date mathematical and statistical methods and information technology. IV. The vegetation classification of Russia will be based on strict rules for naming of syntaxa, according to their validity as formulated in the International Code of Phytosociological Nomenclature, which is constantly being improved (Weber et al., 2020). These underlying principles will help develop the ecological indicative potential of a wide range of vegetation features that can be used to focus on solving a range of global and regional ecology problems, plant resources management, biodiversity protection, and forecasting of the consequences of environmental changes. Prospects for the implementation of the concept «Vegetation classification of Russia» At present, the academic research centers and universities of Moscow, St. Petersburg, Novosibirsk, Vladivostok, Irkutsk, Murmansk, Crimea, Bashkiria, Komi and other regions have sufficient scientific potential to achieve the goals in the framework of the special Program of the Russian Academy of Sciences — that is, to develop a vegetation classification of Russia. To achieve this goal will require: - organization of a network of leading teams within the framework of the Scientific Program of the Russian Academy of Sciences «Vegetation classification of Russia», adjustment of the content of state assignment with the allocation of additional funding. - approval of the thematic Program Committee by the RAS for the development of organizational approaches and elaboration of specific plans for the realization of the Scientific Program, - implementation of the zonal-geographical principle in organization of activity on developing the regional classifications and integrating them into a single classification system of the vegetation of Russia. - ensuring the integration of the system of vegetation classification of Russia with similar systems in the countries of the former USSR, Europe, USA, China, Japan, etc. Potential organizations-participants in the scientific Program — 18 institutes of the Russian Academy of Sciences and 8 Universities. Estimated timelines of the implementation of the concept «Vegetation classification of Russia» — 2021–2030. General schedule for the entire period of research 2021. Approval of classification principles, unified methodical and methodological approaches by project participants. Discussion and elaboration of the rules of organization of the all-Russian archive of geobotanical relevés and syntaxa. 2022–2026. Formation of all-Russian archive of geobotanical relevés and syntaxa. Development of plant community classification and identification of the potential indicative features of units of different ranks based on quantitative methods and comparative syntaxonomic analysis with existing classification systems in Europe, North and East Asia. Justification of new concepts for key syntaxa. The study of environmental and geographical patterns of the vegetation diversity in Russia using up-to-date methods of ordination modeling and botany-geography ana­lysis. 2022. Publication of a Prodromus of vegetation classification of Russia. Schedule for the publication of volumes of the «Vegetation classification of Russia» 2023. «Boreal forests and pre-tundra woodlands» 2024. «Forests of the temperate zone» 2025. «Tundra and polar deserts» and «Alpine ve­getation» 2026. «Steppe vegetation» and «Meadow vegetation» 2027. «Aquatic and bog vegetation» 2028. «Halophytic vegetation» 2029. «Synanthropic vegetation» 2027–2030. Development of criteria for assessing the environmental significance of the plant community syntaxonomic categories for various natural zones based on world criteria. Preparation of the volume «Classification of habitats of Russia and assessment of their environmental significance».

Main text The APMP.QM-S16 comparison was coordinated by the National Institute of Metrology, China (NIM) on behalf of the Technical Committee on Amount of Substance (TCQM) of the Asia Pacific Metrology Programme (APMP) and the Organic Analysis Working Group (OAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) for National Measurement Institutes (NMIs) and Designated Institutes (DIs) which provide measurement services in organic analysis under the 'Comité International des Poids et Mesures' Mutual Recognition Arrangement (CIPM MRA). Fipronil is a broad-spectrum insecticide attributed to the phenylpyrazole family. Due to its high toxicity to invertebrates and long persistence, it has been one of the most widely used insecticides to control household and agricultural pests since its appearance in the market. Fipronil has also shown genotoxicity and cytotoxicity to many vertebrate animals, like mammals, birds, fish, reptiles and so on. Moreover, fipronil could have negative effects on the liver, kidneys and thyroid glands of humans. Its oxidation metabolite is fipronil-sulfone that could induce even higher toxicity than fipronil. In 2017, a fipronil-in-egg scandal occurred in the European Union (EU) that involved more than 15 states. The detected concentration of the sum of fipronil and fipronil-sulfone was many times higher than the EU maximum residue limit in bird egg (5 μg/kg). Besides European countries, fipronil-contaminated eggs were also found in Asian areas like China, Hong Kong and South Korea. Systematic monitoring and control of pesticide residues are necessary to safeguard public health. Fipronil-sulfone was selected to be representative of pesticide residues in this comparison. This study provides the means for assessing measurement capabilities for determination of low-polarity measurands in a procedure that requires extraction, clean-up, analytical separation, and selective detection in a food matrix. Generally, it provides a demonstration of a laboratory's capabilities in determining the medium molecular weight analytes (mass range 300-500) with low polarity (pKow < -2) at mass fraction levels of 4 to 400 μg/kg in a high fat, high protein and low carbohydrate food matrix that falls within Sector 4 of the AOAC Food-matrix Triangle. Seven NMIs/DIs participated in the APMP.QM-S16 comparison. Different methods such as liquid-liquid extraction, QuEChERS and SPE were applied in the sample pre-treatment and HPLC-MS/MS, HPLC-HRMS, and GC-MS/MS were applied for detection by the participants. Most participating laboratories applied isotope dilution mass spectrometry (IDMS) techniques with fipronil-sulfone-13C4,15N2 as internal standard, except EC-JRC-Geel which used matrix matched external calibration method. In the aspect of the traceability for the measurement results, most participants either used their own CRMs, other NMIs' CRMs or the pure materials assessed in-house to guarantee traceability to SI unit. One lab was excluded from the SCRV evaluation, as they did not meet the CIPM metrological traceability requirements. As a result, six sets of valid results were used for the estimation of the SCRV. Finally Hierarchical Bayes was considered to be the appropriate estimator to calculate SCRV, which was determined as 121.82 μg/kg with a standard uncertainty of 1.77 μg/kg. Inspection of the degree of equivalence plots for the fipronil-sulfone mass fraction assignments in APMP.QM-S16 indicated that there was excellent agreement of results. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/. The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

The Key Assignment Scheme (KAS) is a well-studied cryptographic primitive used for hierarchical access control (HAC) in a multilevel organisation where the classes of people with higher privileges can access files of those with lower ones. Our first contribution is the formalization of a new cryptographic primitive, namely, KAS-AE that supports the aforementioned HAC solution with an additional authenticated encryption property. Next, we present three efficient KAS-AE schemes that solve the HAC and the associated authenticated encryption problem more efficiently – both with respect to time and memory – than the existing solutions that achieve it by executing KAS and AE separately. Our first KAS-AE construction is built by using the cryptographic primitive MLE (EUROCRYPT 2013) as a black box; the other two constructions (which are the most efficient ones) have been derived by cleverly tweaking the hash function FP (Indocrypt 2012) and the authenticated encryption scheme APE (FSE 2014). This high efficiency of our constructions is critically achieved by using two techniques: design of a mechanism for reverse decryption used for reduction of time complexity, and a novel key management scheme for optimizing storage requirements when organizational hierarchy forms an arbitrary access graph (instead of a linear graph). We observe that constructing a highly efficient KAS-AE scheme using primitives other than MLE, FP and APE is a non-trivial task. We leave it as an open problem. Finally, we provide a detailed comparison of all the KAS-AE schemes.

A popular cryptographic option to implement Hierarchical Access Control in organizations is to combine a key assignment scheme with a symmetric encryption scheme. In brief, key assignment associates with each object in the hierarchy a unique symmetric key, and provides all higher-ranked “authorized” subjects with a method to recover it. This setup allows for encrypting the payloads associated with the objects so that they can be accessed by the authorized and remain inaccessible for the unauthorized. Both key assignment and symmetric encryption have been researched for roughly four decades now, and a plethora of efficient constructions have been the result. Surprisingly, a treatment of the joint primitive (key assignment combined with encryption, as used in practice) in the framework of provable security was conducted only very recently, leading to a publication in ToSC 2018(4). We first carefully revisit this publication. We then argue that there are actually two standard use cases for the combined primitive, which also require individual treatment. We correspondingly propose a fresh set of security models and provably secure constructions for each of them. Perhaps surprisingly, the two constructions call for different symmetric encryption primitives: While standard AEAD is the right tool for the one, we identify a less common tool called Encryptment as best fitting the other.

Access control is an essential security component of cloud computing, and hierarchical access management is of particular interest because different access privileges are granted in practice. As a solution to versatile and fine-grained hierarchical access control in cloud computing, this paper also presents a hierarchical key assignment scheme based on linear geometry. The encryption key of each class in the hierarchy is connected with a private vector and a public vector in our scheme, and the inner product of an ancestor class's private vector as well as the public variable of its decedent’s class could be used to deduce the encryption method of that descendant class. The proposed scheme is among the direct access strategies on hierarchical access control, which also means so each class at a higher level can straight derive this same encryption key of its decedent’s class without and need to iterate. In furthermore to this basic hierarchy key derivation, we propose a dynamic key management mechanism to handle possible changes in the hierarchy efficiently. Under the assumption of pseudo - random number functions, our scheme requires only light computations over a finite field by providing strong key in-distinguishability. Furthermore, the simulation demonstrates that our scheme maximises the trade-off among computation consumption as well as storage space.

Polish feminist and/or queer groups increasingly endorse the non-hierarchical approach as a working method and a key element of becoming politicized. This approach also tends to serve as a way for such groups to distinguish themselves from other - legally formalized - entities functioning in the same field, such as foundations and associations. Within the Polish queer community, the non-hierarchical approach is presented as a remedy for all forms of domination and injustice, which this community has been mobilized to dismantle. Meanwhile, by replacing formal structures with spontaneously generated bonds of friendship, the groups that embrace the non-hierarchical approach can actually harbor hidden forms of inequality, generating non-democratic practices and condoning the unequal division of labor. An additional problem with the non-hierarchical approach is that, as a stance based on communication and consensus rather than rivalry and winning, it is associated with a traditionally understood "femininity." Thus in initiatives organized around the critique of traditional gender roles (such as feminist and queer groups) this stance is often paradoxically easier to embrace than the need for a clear assignment of functions and responsibilities, despite the fact that the participants of such groups perceive it as a higher stage of development leading to fully egalitarian relations.

AbstractCapacity, reliability, and latency are seen as key requirements of new emerging applications, namely vehicle-to-everything (V2X) and machine-type communication in future cellular networks. D2D communication is envisaged to be the enabler to accomplish the requirements for the applications as mentioned earlier. Due to the scarcity of radio resources, a hierarchical radio resource allocation, namely the sub-granting scheme, has been considered for the overlay D2D communication. In this paper, we investigate the assignment of underutilized radio resources from D2D communication to device-to-infrastructure communication, which are moving in a dynamic environment. The sub-granting assignment problem is cast as a maximization problem of the uplink cell throughput. Firstly, we evaluate the sub-granting signaling overhead due to mobility in a centralized sub-granting resource algorithm, dedicated sub-granting radio resource (DSGRR), and then a distributed heuristics algorithm, open sub-granting radio resource (OSGRR), is proposed and compared with the DSGRR algorithm and no sub-granting case. Simulation results show improved cell throughput for the OSGRR compared with other algorithms. Besides, it is observed that the overhead incurred by the OSGRR is less than the DSGRR while the achieved cell throughput is yet close to the maximum achievable uplink cell throughput.

reason The component of this exploration paper is to show off the maximum essential explanations that set up a fruitful utilization of lean assembling internal assembling SMEs. Plan/philosophy/method-A aggregate of exhaustive writing audit and appearances to ten SMEs located in the south of India have been applied in the examine. The businesses' practices have been apparent to feature the quantity of lean assembling usage internal these agencies. This become trailed by speaking of the pertinent and key organization regarding lean usage. results have been investigated and certified via workshops, contextual analyses and Delphi structures. Discoveries several primary causes that come to a selection the achievement of actualizing the muse of lean assembling internal SMEs are identified. Authority, the board, account hierarchical way of existence and aptitudes and capability among targeted variables; are delegated the maximum relevant issues foremost for the fruitful reception of lean assembling inside SMEs obstacle. take a look at constraints/tips endured suspicion interior SMEs approximately the blessings of safe haven their alternate is a number of the considerable impediments this exploration faces. SMEs are consequently not fairly keen to give important facts and statistics, auspicious for moreover exam. Innovation/esteem The interest of this exploration assignment comes from the acknowledgment of essential factors deciding on an powerful execution of lean assembling interior SMEs trouble. The effects could grant SMEs academic materials and rules for an robust utilization of lean specs. Watchwords Implementation, Lean assembling, SMEs, essential variable

Abstract Key message We evaluate self-organizing maps (SOM) to identify adaptation zones and visualize multi-environment genotypic responses. We apply SOM to multiple traits and crop growth model output of large-scale European sunflower data. Abstract Genotype-by-environment interactions (G × E) complicate the selection of well-adapted varieties. A possible solution is to group trial locations into adaptation zones with G × E occurring mainly between zones. By selecting for good performance inside those zones, response to selection is increased. In this paper, we present a two-step procedure to identify adaptation zones that starts from a self-organizing map (SOM). In the SOM, trials across locations and years are assigned to groups, called units, that are organized on a two-dimensional grid. Units that are further apart contain more distinct trials. In an iterative process of reweighting trial contributions to units, the grid configuration is learnt simultaneously with the trial assignment to units. An aggregation of the units in the SOM by hierarchical clustering then produces environment types, i.e. trials with similar growing conditions. Adaptation zones can subsequently be identified by grouping trial locations with similar distributions of environment types across years. For the construction of SOMs, multiple data types can be combined. We compared environment types and adaptation zones obtained for European sunflower from quantitative traits like yield, oil content, phenology and disease scores with those obtained from environmental indices calculated with the crop growth model Sunflo. We also show how results are affected by input data organization and user-defined weights for genotypes and traits. Adaptation zones for European sunflower as identified by our SOM-based strategy captured substantial genotype-by-location interaction and pointed to trials in Spain, Turkey and South Bulgaria as inducing different genotypic responses.

PurposeBusiness model innovation is a key element for firms' competitiveness. Its development can be supported by the establishment of an actor-oriented scheme to overcome hierarchical structures. The actor-oriented scheme is characterized by intra-organizational networks of relationships that can be established and dissolved between individuals. However, we lack an empirical perspective about its establishment; therefore, the purpose of this research is to advance our understanding of intra-organizational networks for supporting business model innovation.Design/methodology/approachIndividuals create and manage knowledge aimed to innovate the business model through cognitive search and experiential learning mechanisms. Knowledge is spread within organizations by using intra-organizational advice networks, whose patterns reflect the presence of an actor-oriented scheme. This work applies social network analysis to network data from a multi-unit organization specializing in personal care services. We use a Logistic Regression-Quadratic Assignment Procedure to analyze intra-organizational network data on managers' advice exchange related to the learning modes of cognitive search and experiential learning.FindingsOur research empirically identifies the main elements of an actor-oriented scheme in a business model innovation process. We find that managers are able to self-organize, because they are not influenced by their organizational roles, and that commons for sharing resources and protocols, processes and infrastructures enable advice exchange, thus showing the presence of an actor-oriented scheme in business model innovation process.Research limitations/implicationsThis research is based on a cross-sectional database. A longitudinal study would provide a better understanding of the network evolution characterizing the innovation process.Practical implicationsThe results of our study support organizational decision-making for business model innovation.Originality/valueThis study provides empirical evidence of how an actor-oriented scheme emerges in a business model innovation process.