title: Evaluation of Probabilistic Transformations for Evidential Data Association

text: Data association is one of the main tasks to achieve in perception applications. Its aim is to match the sensor detections to the known objects. To treat such issue, recent research focus on the evidential approach using belief functions, which are interpreted as an extension of the probabilistic model for reasoning about uncertainty. The data fusion process begins by quantifying sensor data by belief masses. Thereafter, these masses are combined in order to provide more accurate information. Finally, a probabilistic approximation of these combined masses is done to make-decision on associations. Several probabilistic transformations have been proposed in the literature. However, to the best of our knowledge, these transformations have been evaluated only on simulated examples. For this reason, the objective of this paper is to benchmark most of interesting probabilistic transformations on real-data in order to evaluate their performances for the autonomous vehicle perception problematic.


title: On Semantic Properties of Fuzzy Quantifiers over Fuzzy Universes: Restriction and Living on

text: The article investigates important semantic properties of fuzzy quantifiers, namely restriction and living on a (fuzzy) set. These properties are introduced in the novel frame of fuzzy quantifiers over fuzzy universes.


title: Contextualizing Naive Bayes Predictions

text: A classification process can be seen as a set of actions by which several objects are evaluated in order to predict the class(es) those objects belong to. In situations where transparency is a necessary condition, predictions resulting from a classification process are needed to be interpretable. In this paper, we propose a novel variant of a naive Bayes (NB) classification process that yields such interpretable predictions. In the proposed variant, augmented appraisal degrees (AADs) are used for the contextualization of the evaluations carried out to make the predictions. Since an AAD has been conceived as a mathematical representation of the connotative meaning in an experience-based evaluation, the incorporation of AADs into a NB classification process helps to put the resulting predictions in context. An illustrative example, in which the proposed version of NB classification is used for the categorization of newswire articles, shows how such contextualized predictions can favor their interpretability.


title: Correction of Belief Function to Improve the Performances of a Fusion System

text: Our application concerns the fusion of classifiers for the recognition of trees from their leaves, in the framework of belief functions theory. In order to improve the rate of good classification it is necessary to correct Bayesian mass functions. This correction will be done from the meta-knowledge which is estimated from the confusion matrix. The corrected mass functions considerably improve the recognition rate based on the decisions provided by the classifiers.


title: An Undesirable Behaviour of a Recent Extension of OWA Operators to the Setting of Multidimensional Data

text: OWA operators have been ubiquitous in many disciplines since they were introduced by Yager in 1988. Aside of some other intuitive properties (e.g. monotonicity and idempotence), OWA operators are known to be continuous and, for some carefully constructed weighing vectors, very robust in the presence of outliers. In a recent paper, a natural extension of OWA operators to the setting of multidimensional data has been proposed based on the use of a linear extension of the product order by means of several weighted arithmetic means. Unfortunately, OWA operators constructed in such a way focus too strongly on the level sets of one of the weighted arithmetic means. It is here shown that this focus ultimately results in a forfeit of the properties of continuity and robustness in the presence of outliers.


title: Necessary and Possible Interaction Between Criteria in a General Choquet Integral Model

text: This paper deals with interaction between criteria in a general Choquet integral model. When the preference of the Decision Maker (DM) contains no indifference, we first give a necessary and sufficient condition for them to be representable by a Choquet integral model. Using this condition, we show that it is always possible to choose from the numerical representations, one relatively for which all the Shapley interaction indices are strictly positive. We illustrate our results with an example.


title: Fuzzy Temporal Graphs and Sequence Modelling in Scheduling Problem

text: Processing sequential data and time-dependent data is a problem of constructing computational graph with a certain structure. A computational graph formalizes the structure of a set of computations including mapping temporal inputs and outputs. In this paper we apply graph theory and fuzzy interval representation of uncertain variables to indicate states of the temporal scheduling system. Descriptive model for temporal reasoning on graph, sequence modelling and ordering of fuzzy inputs for scheduling problem is introduced.


title: A Method to Generate Soft Reference Data for Topic Identification

text: Text mining and topic identification models are becoming increasingly relevant to extract value from the huge amount of unstructured textual information that companies obtain from their users and clients nowadays. Soft approaches to these problems are also gaining relevance, as in some contexts it may be unrealistic to assume that any document has to be associated to a single topic without any further consideration of the involved uncertainties. However, there is an almost total lack of reference documents allowing a proper assessment of the performance of soft classifiers in such soft topic identification tasks. To address this lack, in this paper a method is proposed that generates topic identification reference documents with a soft but objective nature, and which proceeds by combining, in random but known proportions, phrases of existing documents dealing with different topics. We also provide a computational study illustrating the application of the proposed method on a well-known benchmark for topic identification, as well as showing the possibility of carrying out an informative evaluation of soft classifiers in the context of soft topic identification.


title: HIV Dynamics Under Antiretroviral Treatment with Interactivity

text: This manuscript presents a model for HIV dynamics of seropositive individuals under antiretroviral treatment described from fuzzy set theory by two different approaches considering interactivity: differential equation with interactive derivative and differential equation with Fréchet derivative. It also establishes an identity between interactive derivative and fuzzy Fréchet derivative. With this identity, we establish when the solutions of the two differential equations coincide. Lastly, we present biological interpretations for both cases.


title: The Necessary and Possible Importance Relation Among Criteria in a 2-Additive Choquet Integral Model

text: In the context of the representation of a preference information by a 2-additive Choquet integral, we introduce the necessary and possible importance relations allowing to compare the Shapley values of two criteria. We present some sufficient conditions, using a set of binary alternatives, to get a necessary importance relation among two criteria.


docid: gqjsuqid

title: Unification in Łukasiewicz Logic with a Finite Number of Variables

text: We prove that the unification type of Łukasiewicz logic with a finite number of variables is either infinitary or nullary. To achieve this result we use Ghilardi’s categorical characterisation of unification types in terms of projective objects, the categorical duality between finitely presented MV-algebras and rational polyhedra, and a homotopy-theoretic argument.


title: A Fuzzy Goal Programming Approach to Fully Fuzzy Linear Regression

text: Traditional linear regression analysis aims at finding a linear functional relationship between predictor and response variables based on available data of a given system, and, when this relationship is found, it is used to predict the future behaviour of the system. The difference between the observed and predicted data is supposed to be due to measurement errors. In fuzzy linear regression, on the other hand, this difference is supposed to be mainly due to the indefiniteness of the system. In this paper, we assume that predictor and response variables are LR-type fuzzy numbers, and so are all regression coefficients; this is known as fully fuzzy linear regression (FFLR) problem. We transform the FFLR problem into a fully fuzzy multiobjective linear programming (FFMOLP) problem. Two fuzzy goal programming methods based on linear and Chebyshev scalarisations are proposed to solve the FFMOLP problem. The proposed methods are compared with a recently published method and show promising results.


title: Towards a Logic-Based View of Some Approaches to Classification Tasks

text: This paper is a plea for revisiting various existing approaches to the handling of data, for classification purposes, based on a set-theoretic view, such as version space learning, formal concept analysis, or analogical proportion-based inference, which rely on different paradigms and motivations and have been developed separately. The paper also exploits the notion of conditional object as a proper tool for modeling if-then rules. It also advocates possibility theory for handling uncertainty in such settings. It is a first, and preliminary, step towards a unified view of what these approaches contribute to machine learning.


title: Towards a Classification of Rough Set Bireducts

text: Size reduction mechanisms are very important in several mathematical fields. In rough set theory, bireducts arose to reduce simultaneously the set of attributes and the set of objects of the considered dataset, providing subsystems with the minimal sets of attributes that connect the maximum number of objects preserving the information of the original dataset. This paper presents the main properties of bireducts and how they can be used for removing inconsistencies.


title: On PSO-Based Approximation of Zadeh’s Extension Principle

text: Zadeh’s extension is a powerful principle in fuzzy set theory which allows to extend a real-valued continuous map to a map having fuzzy sets as its arguments. In our previous work we introduced an algorithm which can compute Zadeh’s extension of given continuous piecewise linear functions and then to simulate fuzzy dynamical systems given by them. The purpose of this work is to present results which generalize our previous approach to a more complex class of maps. For that purpose we present an adaptation on optimization algorithm called particle swarm optimization and demonstrate its use for simulation of fuzzy dynamical systems.


title: Dissimilarity Based Choquet Integrals

text: In this paper, in order to generalize the Choquet integral, we replace the difference between inputs in its definition by a restricted dissimilarity function and refer to the obtained function as d-Choquet integral. For some particular restricted dissimilarity function the corresponding d-Choquet integral with respect to a fuzzy measure is just the ‘standard’ Choquet integral with respect to the same fuzzy measure. Hence, the class of all d-Choquet integrals encompasses the class of all ‘standard’ Choquet integrals. This approach allows us to construct a wide class of new functions, d-Choquet integrals, that are possibly, unlike the ’standard’ Choquet integral, outside of the scope of aggregation functions since the monotonicity is, for some restricted dissimilarity function, violated and also the range of such functions can be wider than [0, 1], in particular it can be [0, n].


title: Intelligent Detection of Information Outliers Using Linguistic Summaries with Non-monotonic Quantifiers

text: In the processing of imprecise information, principally in big data analysis, it is very advantageous to transform numerical values into the standard form of linguistic statements. This paper deals with a novel method of outlier detection using linguistic summaries. Particular attention is devoted to examining the usefulness of non-monotonic quantifiers, which represent a fuzzy determination of the amount of analyzed data. The answer is positive. The use of non-monotonic quantifiers in the detection of outliers can provide a more significant value of the degree of truth of a linguistic summary. At the end, this paper provides a computational example of practical importance.


title: A Study of the Set of Probability Measures Compatible with Comparative Judgements

text: We consider a set of comparative probability judgements over a finite possibility space and study the structure of the set of probability measures that are compatible with them. We relate the existence of some compatible probability measure to Walley’s behavioural theory of imprecise probabilities, and introduce a graphical representation that allows us to bound, and in some cases determine, the extreme points of the set of compatible measures. In doing this, we generalise some earlier work by Miranda and Destercke on elementary comparisons.


title: Imprecise Classification with Non-parametric Predictive Inference

text: In many situations, classifiers predict a set of states of a class variable because there is no information enough to point only one state. In the data mining area, this task is known as Imprecise Classification. Decision Trees that use imprecise probabilities, also known as Credal Decision Trees (CDTs), have been adapted to this field. The adaptation proposed so far uses the Imprecise Dirichlet Model (IDM), a mathematical model of imprecise probabilities that assumes prior knowledge about the data, depending strongly on a hyperparameter. This strong dependence is solved with the Non-Parametric Predictive Inference Model (NPI-M), also based on imprecise probabilities. This model does not make any prior assumption of the data and does not have parameters. In this work, we propose a new adaptation of CDTs to Imprecise Classification based on the NPI-M. An experimental study carried out in this research shows that the adaptation with NPI-M has an equivalent performance than the one obtained with the adaptation based on the IDM with the best choice of the hyperparameter. Consequently, since the NPI-M is a non-parametric approach, it is concluded that the NPI-M is more appropriated than the IDM to be applied to the adaptation of CDTs to Imprecise Classification.


title: Covariate-Adjusted Hybrid Principal Components Analysis

text: Electroencephalography (EEG) studies produce region-referenced functional data in the form of EEG signals recorded across electrodes on the scalp. The high-dimensional data capture underlying neural dynamics and it is of clinical interest to model differences in neurodevelopmental trajectories between diagnostic groups, for example typically developing (TD) children and children with autism spectrum disorder (ASD). In such cases, valid group-level inference requires characterization of the complex EEG dependency structure as well as covariate-dependent heteroscedasticity, such as changes in variation over developmental age. In our motivating study, resting state EEG is collected on both TD and ASD children aged two to twelve years old. The peak alpha frequency (PAF), defined as the location of a prominent peak in the alpha frequency band of the spectral density, is an important biomarker linked to neurodevelopment and is known to shift from lower to higher frequencies as children age. To retain the most amount of information from the data, we model patterns of alpha spectral variation, rather than just the peak location, regionally across the scalp and chronologically across development for both the TD and ASD diagnostic groups. We propose a covariate-adjusted hybrid principal components analysis (CA-HPCA) for region-referenced functional EEG data, which utilizes both vector and functional principal components analysis while simultaneously adjusting for covariate-dependent heteroscedasticity. CA-HPCA assumes the covariance process is weakly separable conditional on observed covariates, allowing for covariate-adjustments to be made on the marginal covariances rather than the full covariance leading to stable and computationally efficient estimation. A mixed effects framework is proposed to estimate the model components coupled with a bootstrap test for group-level inference. The proposed methodology provides novel insights into neurodevelopmental differences between TD and ASD children.


title: Tolerance and Control Solutions of Two-Sided Interval Linear System and Their Applications

text: This work investigates tolerance and control solutions to a two-sided interval linear system. Their semantics are different, even though, we would be able to interchange the role of the interval information algebraically. We present necessary and sufficient conditions of their solvabilities as the inequalities depending on center and radius of coefficient interval matrices on both sides of the system. In a situation when the vector of variables is nonnegative, the conditions can simply be modified as the inequalities depending on boundaries of the interval matrices. This result helps to find out the feasible solutions of a quadratic programming problem with two-sided interval linear equation constraints.


title: Modus Ponens Tollens for RU-Implications

text: In fuzzy rules based systems, fuzzy implication functions are usually considered to model fuzzy conditionals and to perform forward and backward inferences. These processes are guaranteed by the fulfilment of the Modus Ponens and Modus Tollens properties by the fuzzy implication function with respect to the considered conjunction and fuzzy negation. In this paper, we investigate which residual implications derived from uninorms satisfy both Modus Ponens and Modus Tollens properties with respect to the same t-norm and a fuzzy negation simultaneously. The most usual classes of uninorms are considered and many solutions are obtained which allow to model the fuzzy conditionals in a fuzzy rules based systems (and perform backward and forward inferences) with a unique residual implication derived from a uninorm.


title: On Integral Transforms for Residuated Lattice-Valued Functions

text: The article aims to introduce four types of integral transforms for functions whose function values belong to a complete residuated lattice. The integral transforms are defined using so-called qualitative residuum based fuzzy integrals and integral kernels in the form of binary fuzzy relations. We present some of the basic properties of proposed integral transforms including a linearity property that is satisfied under specific conditions for comonotonic functions.


title: A Genetic Approach to the Job Shop Scheduling Problem with Interval Uncertainty

text: In this paper we tackle a variant of the job shop scheduling problem where task durations are uncertain and only an interval of possible values for each task duration is known. We propose a genetic algorithm to minimise the schedule’s makespan that takes into account the problem’s uncertainty during the search process. The behaviour of the algorithm is experimentally evaluated and compared with other state-of-the-art algorithms. Further analysis in terms of solution robustness proves the advantage of taking into account interval uncertainty during the search process with respect to considering only the expected processing times and solving the problem’s crisp counterpart. This robustness analysis also illustrates the relevance of the interval ranking method used to compare schedules during the search.


title: Nonlocal Laplace Operator in a Space with the Fuzzy Partition

text: Differential operators play an important role in the mathematical modeling of dynamic processes and the analysis of various structures. However, there are certain limitations in their use. To remove them, nonlocal differential operators have been proposed. In this work, we focus on nonlocal Laplace operator, which has become increasingly useful in image processing. We introduce the representation of F-transform based Laplace operator in a space with a fuzzy partition. Many useful properties of this operator are proposed and their proofs are also included.


title: Bayesian Smoothing of Decision Tree Soft Predictions and Evidential Evaluation

text: As for many classifiers, decision trees predictions are naturally probabilistic, with a frequentist probability distribution on labels associated to each leaf of the tree. Those probabilities have the major drawback of being potentially unreliable in the case where they have been estimated from a limited number of examples. Empirical Bayes methods enable the updating of observed probability distributions for which the parameters of the prior distribution are estimated from the data. This paper presents an approach of smoothing decision trees predictive binary probabilities with an empirical Bayes method. The update of probability distributions associated with tree leaves creates a correction concentrated on small-sized leaves, which improves the quality of probabilistic tree predictions. The amplitude of these corrections is used to generate predictive belief functions which are finally evaluated through the ensemblist extension of three evaluation indexes of predictive probabilities.


docid: zkhybbzu

title: On the Elicitation of an Optimal Outer Approximation of a Coherent Lower Probability

text: The process of outer approximating a coherent lower probability by a more tractable model with additional properties, such as 2- or completely monotone capacities, may not have a unique solution. In this paper, we investigate whether a number of approaches may help in eliciting a unique outer approximation: minimising a number of distances with respect to the initial model, or maximising the specificity of the outer approximation. We apply these to 2- and completely monotone approximating lower probabilities, and also to possibility measures.


title: Fuzzy Greedy Randomized Adaptive Search Procedure and Simulation Model to Solve the Team Orienteering Problem with Time Windows

text: Tourism is a relevant economic activity that provides important resources (income, employment,...) to countries. When a tourist visits a country or city, he/she wants to know their points of interest. To do this, he/she must select some of the places according to his/her preferences and design routes to visit them. This problem can be adequately modeled as a Team Orienteering Problem with Time Windows (TOPTW). In this paper we propose a fuzzy GRASP and a multi-agent simulation model to solve the TOPTW. Our proposal incorporates two criteria to build the restricted candidate list. The computational results obtained show the validity of the proposal.


title: Metrical Approach to Measuring Uncertainty

text: Many uncertainty measures can be generated by the corresponding divergences, like the Kullback-Leibler divergence generates the Shannon entropy. Divergences can evaluate the information gain obtained by knowing a posterior probability distribution w.r.t. a prior one, or the contradiction between them. Divergences can be also viewed as distances between probability distributions. In this paper, we consider divergences that satisfy a weak system of axioms. This system of axioms does not guaranty additivity of divergences and allows us to consider, for example, the [Formula: see text]-metric on probability measures as a divergence. We show what kind of uncertainty measures can be generated by such divergences, and how these uncertainty measures can be extended to credal sets.


title: A Note on Aggregation of Intuitionistic Values

text: Atanassov’s intuitionistic fuzzy set theory is based on the lattice [Formula: see text] of intuitionistic values and their aggregation. There are lots of works dealing with this topic, but mostly considering some particular cases. In this contribution, we offer a rather general view on aggregation of intuitionistic values with transparent proofs of several properties which significantly shorten the related proofs for particular cases known from the literature.


title: Automorphism Groups of Finite BL-Algebras

text: Using a category dual to finite [Formula: see text]-algebras and their homomorphisms, in this paper we characterise the structure of the automorphism group of any given finite [Formula: see text]-algebra. Further, we specialise our result to the case of the variety generated by the k-element [Formula: see text]-algebra, for each [Formula: see text].


title: A Fuzzy Approach for Similarity Measurement in Time Series, Case Study for Stocks

text: In this paper, we tackle the issue of assessing similarity among time series under the assumption that a time series can be additively decomposed into a trend-cycle and an irregular fluctuation. It has been proved before that the former can be well estimated using the fuzzy transform. In the suggested method, first, we assign to each time series an adjoint one that consists of a sequence of trend-cycle of a time series estimated using fuzzy transform. Then we measure the distance between local trend-cycles. An experiment is conducted to demonstrate the advantages of the suggested method. This method is easy to calculate, well interpretable, and unlike standard euclidean distance, it is robust to outliers.


title: Fast Convergence of Competitive Spiking Neural Networks with Sample-Based Weight Initialization

text: Recent work on spiking neural networks showed good progress towards unsupervised feature learning. In particular, networks called Competitive Spiking Neural Networks (CSNN) achieve reasonable accuracy in classification tasks. However, two major disadvantages limit their practical applications: high computational complexity and slow convergence. While the first problem has partially been addressed with the development of neuromorphic hardware, no work has addressed the latter problem. In this paper we show that the number of samples the CSNN needs to converge can be reduced significantly by a proposed new weight initialization. The proposed method uses input samples as initial values for the connection weights. Surprisingly, this simple initialization reduces the number of training samples needed for convergence by an order of magnitude without loss of accuracy. We use the MNIST dataset to show that the method is robust even when not all classes are seen during initialization.


title: Fuzzy Inference System as an Aggregation Operator - Application to the Design of a Soil Chemical Quality Index

text: Fuzzy logic is widely used in linguistic modeling. In this work, fuzzy logic is used in a multicriteria decision making framework in two different ways. First, fuzzy sets are used to model an expert preference relation for each of the individual information sources to turn raw data into satisfaction degrees. Second, fuzzy rules are used to model the interaction between sources to aggregate the individual degrees into a global score. The whole framework is implemented as an open source software called GeoFIS. The potential of the method is illustrated using an agronomic case study to design a soil chemical quality index from expert knowledge for cacao production systems. The data come from three municipalities of Tolima department in Colombia. The output inferred by the fuzzy inference system was used as a target to learn the weights of classical numerical aggregation operators. Only the Choquet Integral proved to have a similar modeling ability, but the weights would have been difficult to set from expert knowledge without learning.


title: A Word Embedding Model for Mapping Food Composition Databases Using Fuzzy Logic

text: This paper addresses the problem of mapping equivalent items between two databases based on their textual descriptions. Specifically, we will apply this technique to link the elements of two food composition databases by calculating the most likely match of each item in another given database. A number of experiments have been carried by employing different distance metrics, some of them involving Fuzzy Logic. The experiments show that the mappings are highly accurate and Fuzzy Logic improves the precision of the model.


docid: mkmrninv

title: Belief Functions for the Importance Assessment in Multiplex Networks

text: We apply Dempster-Shafer theory in order to reveal important elements in undirected weighted networks. We estimate cooperation of each node with different groups of vertices that surround it via construction of belief functions. The obtained intensities of cooperation are further redistributed over all elements of a particular group of nodes that results in pignistic probabilities of node-to-node interactions. Finally, pairwise interactions can be aggregated into the centrality vector that ranks nodes with respect to derived values. We also adapt the proposed model to multiplex networks. In this type of networks nodes can be differently connected with each other on several levels of interaction. Various combination rules help to analyze such systems as a single entity, that has many advantages in the study of complex systems. In particular, Dempster rule takes into account the inconsistency in initial data that has an impact on the final centrality ranking. We also provide a numerical example that illustrates the distinctive features of the proposed model. Additionally, we establish analytical relations between a proposed measure and classical centrality measures for particular graph configurations.


title: The Formalization of Asymmetry in Disjunctive Evaluation

text: The main property of disjunction is substitutability, i.e., the fully satisfied predicate substitutes the rejected one. But, in many real–world cases disjunction is expressed as the fusion of full and optional alternatives, which is expressed as OR ELSE connective. Generally, this logical connective provides a solution lower than or equal to the MAX operator, and higher than or equal to the projection of the full alternative, i.e., the solution does not go below any averaging function and above MAX function. Therefore, the optional alternative does not influence the solution when it is satisfied with a degree lower than the degree of full alternative. In this work, we propose further generalization by other disjunctive functions in order to allow upward reinforcement of asymmetric disjunction. Finally, the obtained results are illustrated and discussed.


title: A Publicly Available, High Resolution, Unbiased CT Brain Template

text: Clinical imaging relies heavily on X-ray computed tomography (CT) scans for diagnosis and prognosis. Many research applications aim to perform population-level analyses, which require images to be put in the same space, usually defined by a population average, also known as a template. We present an open-source, publicly available, high-resolution CT template. With this template, we provide voxel-wise standard deviation and median images, a basic segmentation of the cerebrospinal fluid spaces, including the ventricles, and a coarse whole brain labeling. This template can be used for spatial normalization of CT scans and research applications, including deep learning. The template was created using an anatomically-unbiased template creation procedure, but is still limited by the population it was derived from, an open CT data set without demographic information. The template and derived images are available at https://github.com/muschellij2/high_res_ct_template. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this chapter (10.1007/978-3-030-50153-2_27) contains supplementary material, which is available to authorized users.


title: Depth-Bounded Approximations of Probability

text: We introduce measures of uncertainty that are based on Depth-Bounded Logics [4] and resemble belief functions. We show that our measures can be seen as approximation of classical probability measures over classical logic, and that a variant of the PSAT [10] problem for them is solvable in polynomial time.


title: Learning Sets of Bayesian Networks

text: This paper considers the problem of learning a generalized credal network (a set of Bayesian networks) from a dataset. It is based on using the BDEu score and computes all the networks with score above a predetermined factor of the optimal one. To avoid the problem of determining the equivalent sample size (ESS), the approach also considers the possibility of an undetermined ESS. Even if the final result is a set of Bayesian networks, the paper also studies the problem of selecting a single network with some alternative procedures. Finally, some preliminary experiments are carried out with three small networks.


title: Aggregation Functions Transformed by 0 - 1 Valued Monotone Systems of Functions

text: In the paper Jin et al. [8] the authors introduced a generalized phi-transformation of aggregation functions. This is a kind of two-step aggregation. This transformation was further developed in Jin et al. [9] into a Generalized-Convex-Sum-Transformation. A special case of the proposed Generalized-Convex-Sum-Transformation is the well-known *-product, also known as the Darsow product of copulas. This approach covers also the discrete Choquet integral. In this paper we study the monotone systems of functions, particularly the case when functions in these systems are just two-valued.


title: Archimedean Choice Functions: An Axiomatic Foundation for Imprecise Decision Making

text: If uncertainty is modelled by a probability measure, decisions are typically made by choosing the option with the highest expected utility. If an imprecise probability model is used instead, this decision rule can be generalised in several ways. We here focus on two such generalisations that apply to sets of probability measures: E-admissibility and maximality. Both of them can be regarded as special instances of so-called choice functions, a very general mathematical framework for decision making. For each of these two decision rules, we provide a set of necessary and sufficient conditions on choice functions that uniquely characterises this rule, thereby providing an axiomatic foundation for imprecise decision making with sets of probabilities. A representation theorem for Archimedean choice functions in terms of coherent lower previsions lies at the basis of both results.


title: Some Remarks on Approximate Reasoning and Bandler-Kohout Subproduct

text: In our contribution we give some remarks and conclusions regarding reasoning schemas used in approximate reasoning. Based on created computer tool for image customization we give some advices regarding FITA. Also, we show some facts regarding Bandler-Kohout subproduct and we present results for several inference schemas.


title: Approximating General Kernels by Extended Fuzzy Measures: Application to Filtering

text: Convolution kernels are essential tools in signal processing: they are used to filter noisy signal, interpolate discrete signals, [Formula: see text]. However, in a given application, it is often hard to select an optimal shape of the kernel. This is why, in practice, it may be useful to possess efficient tools to perform a robustness analysis, talking the form in our case of an imprecise convolution. When convolution kernels are positive, their formal equivalence with probability distributions allows one to use imprecise probability theory to achieve such an imprecise convolution. However, many kernels can have negative values, in which case the previous equivalence does not hold anymore. Yet, we show mathematically in this paper that, while the formal equivalence is lost, the computational tools used to describe sets of probabilities by intervals on the singletons still retain their key properties when used to approximate sets of (possibly) non-positive kernels. We then illustrate their use on a single application that consists of filtering a human electrocardiogram signal by using a low-pass filter whose order is imprecisely known. We show, in this experiment, that the proposed approach leads to tighter bounds than previously proposed approaches.


docid: lrzlmipp

title: On the Properties of Intermediate Quantifiers and the Quantifier “MORE-THAN”

text: This paper continues the research in formal theory of intermediate quantifiers. We present some new properties, introduce intermediate quantifiers of type [Formula: see text], and also new quantifiers MORE-THAN and LESS-THAN.


title: Graded Decagon of Opposition with Fuzzy Quantifier-Based Concept-Forming Operators

text: We introduce twelve operators called fuzzy quantifier-based operators. They are proposed as a new tool to help to deepen the analysis of data in fuzzy formal concept analysis. Moreover, we employ them to construct a graded extension of Aristotle’s square, namely the graded decagon of opposition.


title: Conditioning and Dilation with Coherent Nearly-Linear Models

text: In previous work [1] we introduced Nearly-Linear (NL) models, a class of neighbourhood models obtaining upper/lower probabilities by means of a linear affine transformation (with barriers) of a given probability. NL models are partitioned into more subfamilies, some of which are coherent. One, that of the Vertical Barrier Models (VBM), includes known models, such as the Pari-Mutuel, the [Formula: see text]-contamination or the Total Variation model as special instances. In this paper we study conditioning of coherent NL models, obtaining formulae for their natural extension. We show that VBMs are stable after conditioning, i.e. return a conditional model that is still a VBM, and that this is true also for the special instances mentioned above but not in general for NL models. We then analyse dilation for coherent NL models, a phenomenon that makes our ex-post opinion on an event A, after conditioning it on any event in a partition of hypotheses, vaguer than our ex-ante opinion on A.


docid: kfvqacxb

title: Fuzzy Neighborhood Semantics for Multi-agent Probabilistic Reasoning in Games

text: In this contribution we apply fuzzy neighborhood semantics to multiple agents’ reasoning about each other’s subjective probabilities, especially in game-theoretic situations. The semantic model enables representing various game-theoretic notions such as payoff matrices or Nash equilibria, as well as higher-order probabilistic beliefs of the players about each other’s choice of strategy. In the proposed framework, belief-dependent concepts such as the strategy with the best expected value are formally derivable in higher-order fuzzy logic for any finite matrix game with rational payoffs.


docid: flbiuteu

title: Coherent and Archimedean Choice in General Banach Spaces

text: I introduce and study a new notion of Archimedeanity for binary and non-binary choice between options that live in an abstract Banach space, through a very general class of choice models, called sets of desirable option sets. In order to be able to bring horse lottery options into the fold, I pay special attention to the case where these linear spaces do not include all ‘constant’ options. I consider the frameworks of conservative inference associated with Archimedean choice models, and also pay quite a lot of attention to representation of general (non-binary) choice models in terms of the simpler, binary ones. The representation theorems proved here provide an axiomatic characterisation of, amongst other choice methods, Levi’s E-admissibility and Walley–Sen maximality.


title: General Grouping Functions

text: Some aggregation functions that are not necessarily associative, namely overlap and grouping functions, have called the attention of many researchers in the recent past. This is probably due to the fact that they are a richer class of operators whenever one compares with other classes of aggregation functions, such as t-norms and t-conorms, respectively. In the present work we introduce a more general proposal for disjunctive n-ary aggregation functions entitled general grouping functions, in order to be used in problems that admit n dimensional inputs in a more flexible manner, allowing their application in different contexts. We present some new interesting results, like the characterization of that operator and also provide different construction methods.


title: Secondary Trauma and Parenting Practices in Internet Crimes against Children Task Force Investigators

text: Investigating cases of child pornography requires daily exposure to sexually explicit material involving children and may have negative implications on the mental well-being of those in this line of work. This study aimed to identify whether secondary traumatic stress symptoms were associated with participants’ parenting behaviors and concerns about their own children’s use of the internet. Internet Crimes Against Children Task Force workers (n = 212) completed online questionnaires measuring work exposure to sexually explicit material, secondary traumatic stress symptoms, and parenting behaviors. Professionals in this field reported a wide range of secondary trauma symptoms, and their parenting behaviors were both directly and indirectly (via secondary trauma) affected by prolonged exposure to sexually explicit material involving children. Internet monitoring behaviors were more prevalent for parents of younger children, and mothers’ parenting behaviors were more strongly associated with secondary trauma symptoms than were fathers. Results have implications for mental health and parenting services for professionals in this field.


Looking a Gift Horse in the Mouth: Observations on NHS England's Interim Guidance on Pembrolizumab in Head and Neck Squamous Cell Cancer


Title Page


July/August 2020 Forum


title: Design and Development of Digital Twins: a Case Study in Supply Chains

text: Digital twin technology consists of creating virtual replicas of objects or processes that simulate the behavior of their real counterparts. The objective is to analyze its effectiveness or behavior in certain cases to improve its effectiveness. Applied to products, machines and even complete business ecosystems, the digital twin model can reveal information from the past, optimize the present and even predict the future performance of the different areas analyzed. In the context of supply chains, digital twins are changing the way they do business, providing a range of options to facilitate collaborative environments and data-based decision making and making business processes more robust. This paper proposes the design and development of a digital twin for a case study of a pharmaceutical company. The technology used is based on simulators, solvers and data analytic tools that allow these functions to be connected in an integral interface for the company.


title: Effects of dexmedetomidine on stress hormones in patients undergoing cardiac valve replacement: a randomized controlled trial

text: BACKGROUND: Stress response always occurs in cardiac valve replacement patients undergoing cardiopulmonary bypass (CPB). METHODS: 60 patients undergoing cardiac valve replacement were recruited and randomized into control and Dex groups. Dex group received 1.0 μg·kg-1 of Dex for 10 min intravenously before anesthesia, followed by 0.5 μg·kg-1·h-1 of Dex, steadily administered throughout the procedure. And controlled group received the identical velocity of saline as Dex group. Plasma level of cortisol (Cor), epinephrine (E), norepinephrine (NE), and serotonin (5-HT) were evaluated at four timepoints: Before administration (T0), sawn sternum (T1), end of extracorporeal circulation (T2), and 24 h post operation (T3). General data of operation and recovery such as heart rate (HR), mean arterial pressure (MAP), intraoperative bispectral index (BIS), and hospitalization time in the intensive care unit (ICU) were also compared. RESULTS: Increase of Cor, E, NE, and 5-HT for the Dex group was significant lesser than that in the control group (P < 0.05), and ICU hospitalization time and ventilator support time was significantly shorter in the Dex group. The proportion of patients discharged from the hospital with better prognosis was significantly higher than that in the control group, while there were no significant differences in hospitalization costs and vasoactive drugs use between the two groups. CONCLUSIONS: Dex reduces plasma Cor, E and NE elevations in patients after CPB, alleviates the stress reaction of the body, shortens the hospitalization time and ventilator support time in ICU, and plays a positive role in the rehabilitation of patients undergoing cardiac valve replacement. TRIAL REGISTRATION: China Clinical Trial Registry (No. ChiCTR-IPR-17010954) March 22rd, 2017.


Politik & Management


title: Biology and American Sociology, Part II: Developing a Unique Evolutionary Sociology

text: In sociology’s formative period between 1830 and 1930, evolutionary analysis organized much theorizing and research. This line of work ended abruptly in the 1920s but, over the last decades, has come back into the discipline somewhat piecemeal with the reintroduction of more sophisticated stage models of societal evolution, functional analysis, human ecological analysis, and other new lines of evolutionary inquiry outlined in this paper. Our goal is to demonstrate that revitalized paradigms of the past can still be useful with modest reconceptualization, while at the same time new intellectual movements in the other social sciences, especially economics and psychology, incorporating evolutionary ideas from biology provide sociology with an opportunity to develop its own approach to evolutionary analysis that avoids the problems that let to the demise of this line of inquiry in the 1920s, as well as the problems of other social sciences applying their more narrowly focus models to sociological problems. Indeed, sociology can become a leader in the social sciences in developing more sophisticated theoretical and methodological approaches to incorporating biology and evolutionary analysis into the social sciences. When presented in a new, more sophisticated guise, old approaches like functionalism, stage models of societal evolution, and ecological models can be seen as still having a great deal of explanatory power, while revealing a progressive and future orientation that should appeal to all contemporary sociologists. It is time, then, for sociology to remember its past in order to move into the future.


title: Therapeutic potential of a designed CSαβ peptide ID13 in Staphylococcus aureus-induced endometritis of mice

text: Staphylococcus aureus is a common pathogen that can cause clinical and subclinical endometritis in humans and animals. In this study, a designed CSαβ peptide ID13 from DLP4 exhibited high stable antibacterial activity in simulated gastric fluid (90.79%), serum (99.54%), and different pH buffers (> 99%) against S. aureus CVCC 546 and lower cytotoxicity (89.62% viability) than its parent peptide DLP4 (74.14% viability) toward mouse endometrial epithelial cells (MEECs). ID13 caused a depolarization of bacterial membrane and downregulation of the expression of genes involved in membrane potential maintenance and biofilm formation. The in vitro efficacy analysis of ID13 showed a synergistic effect with vancomycin, ampicillin, rifampin, and ciprofloxacin; intracellular antimicrobial activity against S. aureus CVCC 546 in MEECs; and the ability to inhibit lipoteichoic acid-induced pro-inflammatory cytokines from RAW 264.7. In the S. aureus-induced endometritis of mice, similar to vancomycin, ID13 remarkably alleviated pathological conditions, inhibited the production of cytokines (TNF-α, IL-1ß, IL-6, and IL-10), and suppressed the TLR2-NF-κB signal pathway. Collectively, these results suggest that ID13 could be a potential candidate peptide for therapeutic application in S. aureus-induced endometritis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00253-020-10685-x) contains supplementary material, which is available to authorized users.


Gastrointestinale Manifestation und fäkale Viruslast der SARS-CoV-2-Infektion


docid: esjzqhoo

title: Alles Corona - oder was?


Muskuloskeletale Bewegung und Entzündung im Fokus


CED in Zeiten von COVID-19


title: Phishing Email Detection Based on Binary Search Feature Selection

text: Phishing has appeared as a critical issue in the cybersecurity domain. Phishers adopt email as one of their major channels of communication to lure potential victims. This paper attempts to detect phishing emails by using binary search feature selection (BSFS) with a Pearson correlation coefficient algorithm as a ranking method. The proposed method utilizes four sets of features from the email subject, the body of the email, hyperlinks, and readability of contents. Overall, 41 features were selected from the aforementioned four dimensions. The result shows that the BSFS method evaluated the accuracy of 97.41% in comparison with SFFS (95.63%) and WFS (95.56%). This exploration shows that the SFFS requires more time to ascertain the optimum features set and the WFS requires the least time; however, the accuracy of WFS is very low in comparison with other algorithms. The significant finding of the experiment is that the BFSF requires the least time to evaluate the best feature set with better accuracy even though few features are removed from the feature corpus.


title: Morbidity and mortality in critically ill patients with invasive group A streptococcus infection: an observational study

text: BACKGROUND: Group A streptococci (GAS) are known to cause serious invasive infections, but little is known about outcomes when patients with these infections are admitted to intensive care. We wanted to describe critically ill patients with severe sepsis or septic shock due to invasive GAS (iGAS) and compare them with other patients with severe sepsis or septic shock. METHODS: Adult patients admitted to a general intensive care unit (ICU) in Sweden (2007–2019) were screened for severe sepsis or septic shock according to Sepsis 2 definition. Individuals with iGAS infection were identified. The outcome variables were mortality, days alive and free of vasopressors and invasive mechanical ventilation, maximum acute kidney injury score for creatinine, use of continuous renal replacement therapy and maximum Sequential Organ Failure Assessment score during the ICU stay. Age, Simplified Acute Physiology Score (SAPS 3) and iGAS were used as independent, explanatory variables in regression analysis. Cox regression was used for survival analyses. RESULTS: iGAS was identified in 53 of 1021 (5.2%) patients. Patients with iGAS presented a lower median SAPS 3 score (62 [56–72]) vs 71 [61–81]), p < 0.001), had a higher frequency of cardiovascular cause of admission to the ICU (38 [72%] vs 145 [15%], p < 0.001) and had a higher median creatinine score (173 [100–311] vs 133 [86–208] μmol/L, p < 0.019). Of the GAS isolates, 50% were serotyped emm1/T1 and this group showed signs of more pronounced circulatory and renal failure than patients with non-emm1/T1 (p = 0.036 and p = 0.007, respectively). After correction for severity of illness (SAPS 3) and age, iGAS infection was associated with lower mortality risk (95% confidence interval (CI) of hazard ratio (HR) 0.204–0.746, p < 0.001). Morbidity analyses demonstrated that iGAS patients were more likely to develop renal failure. CONCLUSION: Critically ill patients with iGAS infection had a lower mortality risk but a higher degree of renal failure compared to similarly ill sepsis patients. emm1/T1 was found to be the most dominant serotype, and patients with emm1/T1 demonstrated more circulatory and renal failure than patients with other serotypes of iGAS.


title: Predicting Outcomes After Blunt Chest Trauma—Utility of Thoracic Trauma Severity Score, Cytokines (IL-1β, IL-6, IL-8, IL-10, and TNF-α), and Biomarkers (vWF and CC-16)

text: Thoracic trauma severity score (TTSS) has been used to assess severity and risk of pulmonary complications in patients with chest trauma. The role of cytokines and biomarkers in patients with chest trauma and its association with TTSS is not well elucidated. The aim of the study was to assess the cytokines (IL-1β, IL-6, IL-8, IL-10, and TNF-α) and biomarkers (vWF, CC-16) in patients of thoracic trauma and correlate it with TTSS and patient’s outcome. This was a prospective observational study. Serum and bronchoalveolar lavage fluid samples were collected from chest trauma patients. TTSS was calculated in all patients. Suitable controls for serum and bronchoalveolar lavage (BAL) sample were selected. The outcome parameters included patient discharge or death, duration of hospital, and intensive care unit (ICU) stay. Forty-three patients were included. There was no significant correlation between the measured cytokines and biomarkers and TTSS. The mean TTSS of patients who had a fatal outcome was significantly higher than the patients who recovered. Patients with a high TTSS score had a significant prolonged ICU stay. Patients with a prolonged hospital stay had lower values of CC-16. TTSS is a useful tool to predict severity of chest trauma and prolonged ICU stay. Lower levels of CC-16 in BAL fluid of chest trauma patients were associated with prolonged hospital stay suggestive of its protective role in the airway. Longer prospective studies are required to determine the role of cytokines and biomarkers in patients with thoracic trauma in predicting the patient’s outcome.


title: SURE — EU Capacity for Stabilising Employment and Incomes in the Pandemic

text: On 2 April 2020, the European Commission (2020) duly put forward a proposal for the creation of a European instrument for temporary Support to mitigate Unemployment Risks in an Emergency (SURE). This bold and innovative move must be welcome, but the actual profile of this new instrument requires clarification to avoid misunderstandings, false expectations and eventual disappointment.


title: Why Current EU Proposals for Corona-Related Financial Aid Cannot Replace Coronabonds

text: With public debt-to-GDP levels now set to surpass post-war records and Italy’s ratio approaching levels reached in Greece on the eve of the country’s debt restructuring in early 2012, fears of a return of the sovereign debt crisis have emerged.


The European Response to the Coronavirus Crisis


title: The Privilege of Working From Home at the Time of Social Distancing

text: Although the common perception is that the pandemic is ‘the great equaliser’, workers’ tasks, contractual framework and position in the internal organisational hierarchy strongly affect their ability to work remotely.


title: Slavutych atomograd as the last ideal city of the USSR: Challenges and adaptation mechanisms of resilience

text: Urban resilience implies the ability of all components of a city system to maintain or restore their functions following unforeseen events, and the ability to adapt to external changes. We apply the concept of resilience and adaptation to Slavutych atomograd following the Chornobyl Nuclear Power Station explosion. Challenges and responses facing the urban management and planning systems are examined. Perceptions of Slavutych’s resilience capacity are integrated into research based on a survey of residents. The main challenges faced were lack of targeted financing; insufficient economic diversification and professional employment opportunities; an aging population and outmigration of youth and professionals; physical remoteness from the Kyiv Region; declining quality of municipal infrastructure, poor housing and community services; and slow introduction of market mechanisms. Resilience potential formation is used in effective municipal management practices, stimulating innovations in nuclear/alternative energy, IT, and cultural/artistic events. Urban management and planning systems remain active and are ongoing.


Wound Healing


title: The COVID-19 pandemic: resilient organisational response to a low-chance, high-impact event

text: The global healthcare sector is currently in the midst of the COVID-19 pandemic, a ‘low-chance, high-impact’ event which will require healthcare systems, and the organisations within them, to maintain organisational resilience in order to respond effectively. However, contrary to the instinctive reaction to tighten control, the quality of response depends on healthcare systems’ capacity to loosen control and, subsequently, enhance improvisation. Three factors critical to enhancing an organisation’s capacity for improvisation are highlighted; increasing autonomy, maintaining structure and creating a shared understanding. By drawing on the case of Christchurch Hospital’s response to a major earthquake, this paper demonstrates the vital role that improvisation can play within a clinical setting, when responding to a low-chance, high-impact event.


title: Microneedle Array: Applications, Recent Advances, and Clinical Pertinence in Transdermal Drug Delivery

text: Drug delivery through the skin by transdermal patches has a long history. Subsequent growth of transdermal science proved prominent utility of transdermal systems meant for passive diffusion of the drug. It was followed by the development of iontophoresis- and sonophoresis-based transdermal delivery systems. Microneedle array has now caught attention of the investigators owing to its immense utility in transdermal delivery of very large molecules with ionic and hydrophilic nature. In this technical note, we present the current scenario, applications, and recent advances in microneedle array-based delivery of the most critical molecules through the skin. The application of microneedle has widely been investigated, and these technologies are being developed for the delivery of bio-therapeutics, bio-macromolecules, insulin, growth hormones, immunobiologicals, proteins, siRNA, and peptides. Potential of microneedles to transform the global transdermal market is highlighted in terms of the success rate of the microneedle technologies in clinical trials reaching to the global market. The arrival of the commercial microneedle-based products in the market is highly anticipated as they have potential to portray remarkable impact on clinical medicine in near future.


title: Towards Hypervisor Support for Enhancing the Performance of Virtual Machine Introspection

text: Virtual machine introspection (VMI) is the process of external monitoring of virtual machines. Previous work has demonstrated that VMI can contribute to the security of cloud environments and distributed systems, as it enables, for example, stealthy intrusion detection. One of the biggest challenges for applying VMI in production environments is the performance overhead that certain tracing operations impose on the monitored virtual machine. In this paper, we show how this performance overhead can be significantly minimized by incorporating minor extensions for VMI operations into the hypervisor. In a proof-of-concept implementation, we demonstrate that the pre-processing of VMI events in the Xen hypervisor reduces the monitoring overhead for the use case of VMI-based process-bound monitoring by a factor of 18.


title: Building a Polyglot Data Access Layer for a Low-Code Application Development Platform: (Experience Report)

text: Low-code application development as proposed by the OutSystems Platform enables fast mobile and desktop application development and deployment. It hinges on visual development of the interface and business logic but also on easy integration with data stores and services while delivering robust applications that scale. Data integration increasingly means accessing a variety of NoSQL stores. Unfortunately, the diversity of data and processing models, that make them useful in the first place, is difficult to reconcile with the simplification of abstractions exposed to developers in a low-code platform. Moreover, NoSQL data stores also rely on a variety of general purpose and custom scripting languages as their main interfaces. In this paper we report on building a polyglot data access layer for the OutSystems Platform that uses SQL with optional embedded script snippets to bridge the gap between low-code and full access to NoSQL stores.


docid: budhtlxv

title: Self-tunable DBMS Replication with Reinforcement Learning

text: Fault-tolerance is a core feature in distributed database systems, particularly the ones deployed in cloud environments. The dependability of these systems often relies in middleware components that abstract the DBMS logic from the replication itself. The highly configurable nature of these systems makes their throughput very dependent on the correct tuning for a given workload. Given the high complexity involved, machine learning techniques are often considered to guide the tuning process and decompose the relations established between tuning variables. This paper presents a machine learning mechanism based on reinforcement learning that attaches to a hybrid replication middleware connected to a DBMS to dynamically live-tune the configuration of the middleware according to the workload being processed. Along with the vision for the system, we present a study conducted over a prototype of the self-tuned replication middleware, showcasing the achieved performance improvements and showing that we were able to achieve an improvement of 370.99% on some of the considered metrics.


docid: lqvradqi

title: A Comparison of Message Exchange Patterns in BFT Protocols: (Experience Report)

text: The performance and scalability of byzantine fault-tolerant (BFT) protocols for state machine replication (SMR) have recently come under scrutiny due to their application in the consensus mechanism of blockchain implementations. This led to a proliferation of proposals that provide different trade-offs that are not easily compared as, even if these are all based on message passing, multiple design and implementation factors besides the message exchange pattern differ between each of them. In this paper we focus on the impact of different combinations of cryptographic primitives and the message exchange pattern used to collect and disseminate votes, a key aspect for performance and scalability. By measuring this aspect in isolation and in a common framework, we characterise the design space and point out research directions for adaptive protocols that provide the best trade-off for each environment and workload combination.


title: A Resource Usage Efficient Distributed Allocation Algorithm for 5G Service Function Chains

text: Recent evolution of networks introduce new challenges for the allocation of resources. Slicing in 5G networks allows multiple users to share a common infrastructure and the chaining of Network Function (NFs) introduces constraints on the order in which NFs are allocated. We first model the allocation of resources for Chains of NFs in 5G Slices. Then we introduce a distributed mutual exclusion algorithm to address the problem of the allocation of resources. We show with selected metrics that choosing an order of allocation of the resources that differs from the order in which resources are used can give better performances. We then show experimental results where we improve the usage rate of resources by more than 20% compared to the baseline algorithm in some cases. The experiments run on our own simulator based on SimGrid.


title: Capturing Privacy-Preserving User Contexts with IndoorHash

text: IoT devices are ubiquitous and widely adopted by end-users to gather personal and environmental data that often need to be put into context in order to gain insights. In particular, location is often a critical context information that is required by third parties in order to analyse such data at scale. However, sharing this information is i) sensitive for the user privacy and ii) hard to capture when considering indoor environments. This paper therefore addresses the challenge of producing a new location hash, named IndoorHash, that captures the indoor location of a user, without disclosing the physical coordinates, thus preserving their privacy. This location hash leverages surrounding infrastructure, such as WiFi access points, to compute a key that uniquely identifies an indoor location. Location hashes are only known from users physically visiting these locations, thus enabling a new generation of privacy-preserving crowdsourcing mobile applications that protect from third parties re-identification attacks. We validate our results with a crowdsourcing campaign of 31 mobile devices during one month of data collection.


title: On the Trade-Offs of Combining Multiple Secure Processing Primitives for Data Analytics

text: Cloud Computing services for data analytics are increasingly being sought by companies to extract value from large quantities of information. However, processing data from individuals and companies in third-party infrastructures raises several privacy concerns. To this end, different secure analytics techniques and systems have recently emerged. These initial proposals leverage specific cryptographic primitives lacking generality and thus having their application restricted to particular application scenarios. In this work, we contribute to this thriving body of knowledge by combining two complementary approaches to process sensitive data. We present SafeSpark, a secure data analytics framework that enables the combination of different cryptographic processing techniques with hardware-based protected environments for privacy-preserving data storage and processing. SafeSpark is modular and extensible therefore adapting to data analytics applications with different performance, security and functionality requirements. We have implemented a SafeSpark’s prototype based on Spark SQL and Intel SGX hardware. It has been evaluated with the TPC-DS Benchmark under three scenarios using different cryptographic primitives and secure hardware configurations. These scenarios provide a particular set of security guarantees and yield distinct performance impact, with overheads ranging from as low as 10% to an acceptable 300% when compared to an insecure vanilla deployment of Apache Spark.


title: TailX: Scheduling Heterogeneous Multiget Queries to Improve Tail Latencies in Key-Value Stores

text: Users of interactive services such as e-commerce platforms have high expectations for the performance and responsiveness of these services. Tail latency, denoting the worst service times, contributes greatly to user dissatisfaction and should be minimized. Maintaining low tail latency for interactive services is challenging because a request is not complete until all its operations are completed. The challenge is to identify bottleneck operations and schedule them on uncoordinated backend servers with minimal overhead, when the duration of these operations are heterogeneous and unpredictable. In this paper, we focus on improving the latency of multiget operations in cloud data stores. We present TailX, a task-aware multiget scheduling algorithm that improves tail latencies under heterogeneous workloads. TailX schedules operations according to an estimation of the size of the corresponding data, and allows itself to procrastinate some operations to give way to higher priority ones. We implement TailX in Cassandra, a widely used key-value store. The result is an improved overall performance of the cloud data stores for a wide variety of heterogeneous workloads. Specifically, our experiments under heterogeneous YCSB workloads show that TailX outperforms state-of-the-art solutions and reduces tail latencies by up to 70% and median latencies by up to 75%.


title: Fed-DIC: Diagonally Interleaved Coding in a Federated Cloud Environment

text: Coping with failures in modern distributed storage systems that handle massive volumes of heterogeneous and potentially rapidly changing data, has become a very important challenge. A common practice is to utilize fault tolerance methods like Replication and Erasure Coding for maximizing data availability. However, while erasure codes provide better fault tolerance compared to replication with a more affordable storage overhead, they frequently suffer from high reconstruction cost as they require to access all available nodes when a data block needs to be repaired, and also can repair up to a limited number of unavailable data blocks, depending on the number of the code’s parity block capabilities. Furthermore, storing and placing the encoded data in the federated storage system also remains a challenge. In this paper we present Fed-DIC, a framework which combines Diagonally Interleaved Coding on client devices at the edge of the network with organized storage of encoded data in a federated cloud system comprised of multiple independent storage clusters. The erasure coding operations are performed on client devices at the edge while they interact with the federated cloud to store the encoded data. We describe how our solution integrates the functionality of federated clouds alongside erasure coding implemented on edge devices for maximizing data availability and we evaluate the working and benefits of our approach in terms of read access cost, data availability, storage overhead, load balancing and network bandwidth rate compared to popular Replication and Erasure Coding schemes.


title: Kollaps/Thunderstorm: Reproducible Evaluation of Distributed Systems: Tutorial Paper

text: Reproducing experimental results is nowadays seen as one of the greatest impairments for the progress of science in general and distributed systems in particular. This stems from the increasing complexity of the systems under study and the inherent complexity of capturing and controlling all variables that can potentially affect experimental results. We argue that this can only be addressed with a systematic approach to all the stages and aspects of the evaluation process, such as the environment in which the experiment is run, the configuration and software versions used, and the network characteristics among others. In this tutorial paper, we focus on the networking aspect, and discuss our ongoing research efforts and tools to contribute to a more systematic and reproducible evaluation of large scale distributed systems.


title: A Self-stabilizing One-To-Many Node Disjoint Paths Routing Algorithm in Star Networks

text: The purpose of the paper is to present the first self-stabilizing algorithm for finding [Formula: see text] one-to-many node-disjoint paths in message passing model. Two paths in a network are said to be node disjoint if they do not share any nodes except for the endpoints. Our proposed algorithm works on n-dimensional star networks [Formula: see text]. Given a source node s and a set of [Formula: see text] of [Formula: see text] destination nodes in the n-dimensional star network, our algorithm constructs [Formula: see text] node-disjoints paths [Formula: see text], where [Formula: see text] is a path from s to [Formula: see text], [Formula: see text]. Since the proposed solution is self-stabilizing [7], it does not require initialization and withstands transient faults. The stabilization time of our algorithm is [Formula: see text] rounds.


title: DroidAutoML: A Microservice Architecture to Automate the Evaluation of Android Machine Learning Detection Systems

text: The mobile ecosystem is witnessing an unprecedented increase in the number of malware in the wild. To fight this threat, actors from both research and industry are constantly innovating to bring concrete solutions to improve security and malware protection. Traditional solutions such as signature-based anti viruses have shown their limits in front of massive proliferation of new malware, which are most often only variants specifically designed to bypass signature-based detection. Accordingly, it paves the way to the emergence of new approaches based on Machine Learning (ML) technics to boost the detection of unknown malware variants. Unfortunately, these solutions are most often underexploited due to the time and resource costs required to adequately fine tune machine learning algorithms. In reality, in the Android community, state-of-the-art studies do not focus on model training, and most often go through an empirical study with a manual process to choose the learning strategy, and/or use default values as parameters to configure ML algorithms. However, in the ML domain, it is well known admitted that to solve efficiently a ML problem, the tunability of hyper-parameters is of the utmost importance. Nevertheless, as soon as the targeted ML problem involves a massive amount of data, there is a strong tension between feasibility of exploring all combinations and accuracy. This tension imposes to automate the search for optimal hyper-parameters applied to ML algorithms, that is not anymore possible to achieve manually. To this end, we propose a generic and scalable solution to automatically both configure and evaluate ML algorithms to efficiently detect Android malware detection systems. Our approach is based on devOps principles and a microservice architecture deployed over a set of nodes to scale and exhaustively test a large number of ML algorithms and hyper-parameters combinations. With our approach, we are able to systematically find the best fit to increase up to 11% the accuracy of two state-of-the-art Android malware detection systems.


title: Chemoprevention in familial adenomatous polyposis: past, present and future

text: Familial adenomatous polyposis (FAP) is a hereditary colorectal cancer syndrome characterized by colorectal adenomas and a near 100% lifetime risk of colorectal cancer (CRC). Prophylactic colectomy, usually by age 40, is the gold-standard therapy to mitigate this risk. However, colectomy is associated with morbidity and fails to prevent extra-colonic disease manifestations, including gastric polyposis, duodenal polyposis and cancer, thyroid cancer, and desmoid disease. Substantial research has investigated chemoprevention medications in an aim to prevent disease progression, postponing the need for colectomy and temporizing the development of extracolonic disease. An ideal chemoprevention agent should have a biologically plausible mechanism of action, be safe and easily tolerated over a prolonged treatment period, and produce a durable and clinically meaningful effect. To date, no chemoprevention agent tested has fulfilled these criteria. New agents targeting novel pathways in FAP are needed. Substantial preclinical literature exists linking the molecular target of rapamycin (mTOR) pathway to FAP. A single case report of rapamycin, an mTOR inhibitor, used as chemoprevention in FAP patients exists, but no formal clinical studies have been conducted. Here, we review the prior literature on chemoprevention in FAP, discuss the rationale for rapamycin in FAP, and outline a proposed clinical trial testing rapamycin as a chemoprevention agent in patients with FAP.


Fighting the Moral Distress of Idleness


title: Annex: Krisenpflichten in der Corona-Krise

text: Im März 2020 hat der Gesetzgeber ein umfangreiches Maßnahmenpaket zur Abmilderung der juristischen und wirtschaftlichen Folgen der Corona-Pandemie beschlossen. Hieraus ergeben sich Konsequenzen für die in der unternehmenskrise zu beachtenden Pflichten, insbesondere für die Antragspflicht (Kap. 9) und das Zahlungsverbot (Kap. 11).


Editorial note


Ground glass: the future after COVID‐19?


title: Meet COVID‐19 challenges with enthusiasm, strong communication

text: James Gilman graduated from the University of New Haven in 1993. After he'd worked for the Connecticut State Police for 22 years, he returned to his alma mater, this time as the Chief of Police. “It was very exciting to get back to where I started,” Gilman said.


The China–US blame game: claims‐making about the origin of a new virus


Religious returns, ritual changes and divinations on COVID‐19


Viral living


From sociality to social distancing: reversing values of solidarity in Italy


Pandemic vulnerabilities, mortality and empathy in fieldwork


Life versus capital: COVID‐19 and the politics of life


What does COVID‐19 distract us from? A migration studies perspective on the inequities of attention


title: Keep your mission student‐centered, even in the face of crisis

text: Jay Gatrell, Ph.D., Provost and Vice President for Academic Affairs at Eastern Illinois University, understands what it means to really live out the mission of his institution in everything he does. Gatrell spent 14 years of his academic career at Indiana State University, an opportunity that afforded him the chance to work in many different roles of academic leadership, including Associate Dean, Interim Chair, Acting Chair, and Dean of the Graduate School and Chief Research Officer.


Letter from the (un)seen virus: (post)humanist perspective in corona times


title: Rethink management, operation of college sports in light of COVID‐19 pandemic

text: As the world continues to confront COVID‐19, every governing body, conference, and association, and virtually every collegiate institution, continues to carefully monitor, evaluate, and consider both the current situation and their next steps.


docid: lowtjinw

title: All in this together? Isolation and housing in ‘lockdown London’


COVID‐19 and climate change reactions: STS potential of online research


Reclaiming the social from ‘social distancing’


title: Adapt to the daily operations of campus security in the wake of COVID‐19

text: The COVID‐19 pandemic has upended the normal routines of colleges and universities across the nation. Campus security departments are no exception. With fewer people on campus, their responsibilities have changed but not lessened. Campus security leaders must also consider the health threats posed to their own staff as they make assignments and monitor the unfolding pandemic.


title: Consider role of contractual obligations in decision‐making during times of crisis

text: The global crisis brought on by the COVID‐19 pandemic has forever changed higher education. In the beginning of the crisis, leaders on college campuses had to decide what to do with courses, students in residence halls, auxiliary services like food operations and bookstores, scheduled athletics competitions, and full‐time faculty and staff who normally reported to physical buildings. And those are just the obvious examples.


Jishuku, social distancing and care in the time of COVID‐19 in Japan


title: COVID‐19 will change our campuses forever

text: Every three months when I sit down to write this column, I always try to choose a contemporary topic that, even though I am writing a few months ahead of publication, will still be relevant when readers see it. But as I pen this piece, I have never felt more confident that, when this column publishes, COVID‐19 will still be on everyone's mind.


Open Access, Open Science, and Coronavirus: Mega trends with historical proportions


Touch in the new ‘1.5‐metre society’


Fear of others: thinking biopolitics


title: Virtual APA meeting: Importance of helping pregnancy women with SUDs

text: In “Substance Use Disorders in Perinatal Women,” Kimberly Yonkers, M.D., gives a sobering presentation on the consequences of substance use in pregnant women, on the women themselves, their pregnancies, and their offspring, in the perinatal period. Yonkers' presentation took place April 25 as part of the American Psychiatric Association's (APA's) virtual online annual meeting; the meeting itself, scheduled to be in Philadelphia, was canceled due to COVID‐19. Yonkers' presentation touched on social justice as well as medical issues.


The coronavirus hit us strong: a small‐scale narrative


When rumours fly like helicopters: an international conspiracy ‘language’ for the new reality?


title: Reverse design of an influenza neutralizing spiky nano‐inhibitor with a dual mode of action

text: In this study, we demonstrate the concept of ‘reverse design’ for virus inhibitors. With the current knowledge of influenza A virus (IAV), we designed a nano‐inhibitor that has a reverse shape to the viral particle and heteromultivalent inhibitory effects on hemagglutinin and neuraminidase. The synthesized nano‐inhibitor can neutralize the viral particle extracellularly and block its attachment and entry to the host cells. The virus replication was significantly reduced by 6 orders of magnitude in the presence of the reverse designed nano‐inhibitors. Even being used 24 hours after the infection, >99.999% inhibition is also achieved, which indicates such a nano‐inhibitor might be a potent antiviral for the treatment of influenza infection.


Bericht aus dem Vorstand der ÖGKJP


title: Predicting the outcomes of preterm neonates beyond the neonatal intensive care unit: What are we missing?

text: ABSTRACT: Preterm infants are a population at high risk for mortality and adverse health outcomes. With recent improvements in survival to childhood, increasing attention is being paid to risk of long-term morbidity, specifically during childhood and young-adulthood. Although numerous tools for predicting the functional outcomes of preterm neonates have been developed in the past three decades, no studies have provided a comprehensive overview of these tools, along with their strengths and weaknesses. The purpose of this article is to provide an in-depth, narrative review of the current risk models available for predicting the functional outcomes of preterm neonates. A total of 32 studies describing 43 separate models were considered. We found that most studies used similar physiologic variables and standard regression techniques to develop models that primarily predict the risk of poor neurodevelopmental outcomes. With a recently expanded knowledge regarding the many factors that affect neurodevelopment and other important outcomes, as well as a better understanding of the limitations of traditional analytic methods, we argue that there is great room for improvement in creating risk prediction tools for preterm neonates. We also consider the ethical implications of utilizing these tools for clinical decision-making. IMPACT: Based on a literature review of risk prediction models for preterm neonates predicting functional outcomes, future models should aim for more consistent outcomes definitions, standardized assessment schedules and measurement tools, and consideration of risk beyond physiologic antecedents. Our review provides a comprehensive analysis and critique of risk prediction models developed for preterm neonates, specifically predicting functional outcomes instead of mortality, to reveal areas of improvement for future studies aiming to develop risk prediction tools for this population. To our knowledge, this is the first literature review and narrative analysis of risk prediction models for preterm neonates regarding their functional outcomes.


Health-related quality of life after critical care—the emperor’s new clothes


title: Multiple cross displacement amplification-a more applicable technique in detecting Pseudomonas aeruginosa of ventilator-associated pneumonia (VAP)

text: BACKGROUND: Early and rapid identification of Pseudomonas aeruginosa (P. aeruginosa) in patients with suspected ventilator-associated pneumonia (VAP) provides theoretical clinical advantages in therapeutic optimization strategies. METHODS: The P. aeruginosa-multiple cross displacement amplification (PA-MCDA) assay was conducted at an isothermal temperature during the amplification stage, and products were visually detected by color changes. The entire process was completed within 1 h. A total of 77 strains, including P. aeruginosa species and various other species of non-P. aeruginosa, were used to evaluate PA-MCDA assays. Bronchoalveolar lavage fluid (BALF) of suspected VAP patients was examined by the MCDA assay. RESULTS: The MCDA assay exhibited a 100% analytical specificity in detecting PA from all 77 strains, and the limit of detection was as low as 100 fg DNA per reaction. A temperature of 65 °C was recommended as standard during the amplification stage. The agreement between PA-MCDA and bacteria culture was 91.18% (κ = 0.787; p = 0.000) in the identification of P. aeruginosa in BALF from suspected VAP. The PA-MCDA assay showed values of 92.31%, 90.78%, 77.41%, and 97.18% for sensitivity, specificity, positive predictive value, and negative predictive value, respectively. PA-MCDA had a higher detective rate of P. aeruginosa than bacteria culture in patients with antipseudomonal therapy. CONCLUSIONS: The instrument-free platform of the MCDA assay makes it a simple, rapid, and applicable procedure for “on-site” diagnosis and point-of-care testing for the presence of P. aeruginosa without the need for specific bacterial culture.


Bericht aus dem Vorstand


docid: mtjughzl

title: The SARS-CoV-2 Ivermectin Navarra-ISGlobal Trial (SAINT) to Evaluate the Potential of Ivermectin to Reduce COVID-19 Transmission in low risk, non-severe COVID-19 patients in the first 48 hours after symptoms onset: A structured summary of a study protocol for a randomized control pilot trial

text: OBJECTIVES: The primary objective is to determine the efficacy of a single dose of ivermectin, administered to low risk, non-severe COVID-19 patients in the first 48 hours after symptom onset to reduce the proportion of patients with detectable SARS-CoV-2 RNA by Polymerase Chain Reaction (PCR) test from nasopharyngeal swab at day 7 post-treatment. 1. To assess the efficacy of ivermectin to reduce the SARS-CoV-2 viral load in the nasopharyngeal swab at day 7 post treatment. 2. To assess the efficacy of ivermectin to improve symptom progression in treated patients. 3. To assess the proportion of seroconversions in treated patients at day 21. 4. To assess the safety of ivermectin at the proposed dose. 5. To determine the magnitude of immune response against SARS-CoV-2. 6. To assess the early kinetics of immunity against SARS-CoV-2. TRIAL DESIGN: SAINT is a single centre, double-blind, randomized, placebo-controlled, superiority trial with two parallel arms. Participants will be randomized to receive a single dose of 400 μg/kg ivermectin or placebo, and the number of patients in the treatment and placebo groups will be the same (1:1 ratio). PARTICIPANTS: The population for the study will be patients with a positive nasopharyngeal swab PCR test for SARS-CoV-2, with non-severe COVID-19 disease, and no risk factors for progression to severity. Vulnerable populations such as pregnant women, minors (i.e.; under 18 years old), and seniors (i.e.; over 60 years old) will be excluded. Inclusion criteria: 1. Patients diagnosed with COVID-19 in the emergency room of the Clínica Universidad de Navarra (CUN) with a positive SARS-CoV-2 PCR. 2. Residents of the Pamplona basin (“Cuenca de Pamplona”). 3. The patient must be between the ages of 18 and 60 years of age. 4. Negative pregnancy test for women of child bearing age*. 5. The patient or his/her representative, has given informed consent to participate in the study. 6. The patient should, in the PI's opinion, be able to comply with all the requirements of the clinical trial (including home follow up during isolation). Exclusion criteria: 1. Known history of ivermectin allergy. 2. Hypersensitivity to any component of ivermectin. 3. Diagnosed by the attending physician. Identified in a chest X-ray. 4. Fever or cough present for more than 48 hours. 5. Positive IgG against SARS-CoV-2 by rapid diagnostic test. 6. Age under 18 or over 60 years. 7. Immunosuppression. Chronic Obstructive Pulmonary Disease. Diabetes. Hypertension. Obesity. Acute or chronic renal failure. History of coronary disease. History of cerebrovascular disease. Current neoplasm. 8. Recent travel history to countries that are endemic for Loa loa (Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Ethiopia, Equatorial, Guinea, Gabon, Republic of Congo, Nigeria and Sudan). 9. Current use of CYP 3A4 or P-gp inhibitor drugs such as quinidine, amiodarone, diltiazem, spironolactone, verapamil, clarithromycin, erythromycin, itraconazole, ketoconazole, cyclosporine, tacrolimus, indinavir, ritonavir or cobicistat. Use of critical CYP3A4 substrate drugs such as warfarin. *Women of child bearing age may participate if they use a safe contraceptive method for the entire period of the study and at least one month afterwards. A woman is considered to not have childbearing capacity if she is post-menopausal (minimum of 2 years without menstruation) or has undergone surgical sterilization (at least one month before the study). The trial is currently planned at a single center, Clínica Universidad de Navarra, in Navarra (Spain), and the immunology samples will be analyzed at the Barcelona Institute for Global Health (ISGlobal), in Barcelona (Spain). Participants will be recruited by the investigators at the emergency room and/or COVID-19 area of the CUN. They will remain in the trial for a period of 28 days at their homes since they will be patients with mild disease. In the interest of public health and to contain transmission of infection, follow-up visits will be conducted in the participant's home by a clinical trial team comprising nursing and medical members. Home visits will assess clinical and laboratory parameters of the patients. INTERVENTION AND COMPARATOR: Ivermectin will be administered to the treatment group at a 400μg/Kg dose (included in the EU approved label of Stromectol and Scabioral). The control group will receive placebo. There is no current data on the efficacy of ivermectin against the virus in vivo, therefore the use of placebo in the control group is ethically justified. MAIN OUTCOMES: Primary Proportion of patients with a positive SARS-CoV-2 PCR from a nasopharyngeal swab at day 7 post-treatment. : 1. Mean viral load as determined by PCR cycle threshold (Ct) at baseline and on days 4, 7, 14, and 21. 2. Proportion of patients with fever and cough at days 4, 7, 14, and 21 as well as proportion of patients progressing to severe disease or death during the trial. 3. Proportion of patients with seroconversion at day 21. 4. Proportion of drug-related adverse events during the trial. 5. Median levels of IgG, IgM, IgA measured by Luminex, frequencies of innate and SARS-CoV-2-specific T cells assessed by flow cytometry, median levels of inflammatory and activation markers measured by Luminex and transcriptomics. 6. Median kinetics of IgG, IgM, IgA levels during the trial, until day 28. RANDOMISATION: Eligible patients will be allocated in a 1:1 ratio using a randomization list generated by the trial statistician using blocks of four to ensure balance between the groups. A study identification code with the format “SAINT-##” (##: from 01 to 24) will be generated using a sequence of random numbers so that the randomization number does not match the subject identifier. The sequence and code used will be kept in an encrypted file accessible only to the trial statistician. A physical copy will be kept in a locked cabinet at the CUN, accessible only to the person administering the drug who will not enrol or attend to patient care. A separate set of 24 envelopes for emergency unblinding will be kept in the study file. BLINDING (MASKING): The clinical trial team and the patients will be blinded. The placebo will not be visibly identical, but it will be administered by staff not involved in the clinical care or participant follow up. NUMBERS TO BE RANDOMISED (SAMPLE SIZE): The sample size is 24 patients: 12 participants will be randomised to the treatment group and 12 participants to the control group. TRIAL STATUS: Current protocol version: 1.0 dated 16 of April 2020. Recruitment is envisioned to begin by May 14th and end by June 14th. TRIAL REGISTRATION: EudraCT number: 2020-001474-29, registered April 1(st). Clinicaltrials.gov: submitted, pending number FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.


title: Intracranial-to-central venous pressure gap predicts the responsiveness of intracranial pressure to PEEP in patients with traumatic brain injury: a prospective cohort study

text: BACKGROUND: Mechanical ventilation (MV) with positive end-expiratory pressure (PEEP) is commonly applied in patients with severe traumatic brain injury (sTBI). However, the individual responsiveness of intracranial pressure (ICP) to PEEP varies. Thus, identifying an indicator detecting ICP responsiveness to PEEP is of great significance. As central venous pressure (CVP) could act as an intermediary to transduce pressure from PEEP to ICP, we developed a new indicator, P(IC)Gap, representing the gap between baseline ICP and baseline CVP. The aim of the current study was to explore the relationship between P(IC)Gap and ICP responsiveness to PEEP. METHODS: A total of 112 patients with sTBI undergoing MV were enrolled in this prospective cohort study. ICP, CVP, cerebral perfusion pressure (CPP), static compliance of the respiratory system (Cst), and end-tidal carbon dioxide pressure (PetCO(2)) were recorded at the initial (3 cmH(2)O) and adjusted (15 cmH(2)O) levels of PEEP. P(IC)Gap was assessed as baseline ICP - baseline CVP (when PEEP = 3 cmH(2)O). The patients were classified into the ICP responder and non-responder groups based on whether ICP increment with PEEP adjusted from 3 cmH(2)O to 15 cmH(2)O was greater than 20% of baseline ICP. The above parameters were compared between the two groups, and prediction of ICP responsiveness to PEEP adjustment was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: Compared with the non-responder group, the responder group had lower P(IC)Gap (1.63 ± 1.33 versus 6.56 ± 2.46 mmHg; p < 0.001), lower baseline ICP, and higher baseline CVP. ROC curve analysis suggested that P(IC)Gap was a stronger predictive indicator of ICP responsiveness to PEEP (AUC = 0.957, 95%CI 0.918–0.996; p < 0.001) compared with baseline ICP and baseline CVP, with favorable sensitivity (95.24, 95%CI 86.91–98.70%) and specificity (87.6, 95%CI 75.76–94.27%), at a cut off value of 2.5 mmHg. CONCLUSION: The impact of PEEP on ICP depends on the gap between baseline ICP and baseline CVP, i.e. P(IC)Gap. In addition, P(IC)Gap is a potential predictor of ICP responsiveness to PEEP adjustment in patients with sTBI.


title: Futuristic CRISPR-based biosensing in the cloud and internet of things era: an overview

text: Biosensors-based devices are transforming medical diagnosis of diseases and monitoring of patient signals. The development of smart and automated molecular diagnostic tools equipped with biomedical big data analysis, cloud computing and medical artificial intelligence can be an ideal approach for the detection and monitoring of diseases, precise therapy, and storage of data over the cloud for supportive decisions. This review focused on the use of machine learning approaches for the development of futuristic CRISPR-biosensors based on microchips and the use of Internet of Things for wireless transmission of signals over the cloud for support decision making. The present review also discussed the discovery of CRISPR, its usage as a gene editing tool, and the CRISPR-based biosensors with high sensitivity of Attomolar (10(−18)M), Femtomolar (10(−15)M) and Picomolar (10(−12)M) in comparison to conventional biosensors with sensitivity of nanomolar 10(−9)M and micromolar 10(−3)M. Additionally, the review also outlines limitations and open research issues in the current state of CRISPR-based biosensing applications.


title: Barriers and challenges in the process of including critically ill patients in clinical studies

text: BACKGROUND: Clinical research in severely ill or injured patients is required to improve healthcare but may be challenging to perform in practice. The aim of this study was to analyse barriers and challenges in the process of including critically ill patients in clinical studies. METHODS: Data from critically ill patients considered for inclusion in an observational study of venous thromboembolism in Norway were analysed. This included quantitative and qualitative information from the screening log, consent forms and research notes. RESULTS: Among 279 eligible critically ill patients, 204 (73%) were omitted from the study due to challenges and barriers in the inclusion process. Reasons for omission were categorised as practical in 133 (65%), medical in 31 (15%), and legal or ethical in 40 (20%) of the patients. Among 70 included patients, 29 (41%) consents were from patients and 41 (59%) from their next of kin. Several challenges were described herein; these included whether patients were competent to give consent, and which next of kin that should represent the patient. Furthermore, some included patients were unable to recall what they have consented, and some appeared unable to separate research from treatment. CONCLUSIONS: Barriers and challenges in the inclusion process led to the omission of near three out of four eligible patients. This analysis provided information about where the problem resides and may be solved. The majority of challenges among included patients were related to issues of autonomy and validity of consent. TRIAL REGISTRATION: ClinicalTrials.gov (NCT03405766).