Hierarchical Bayesian classification methods to identify topics by journal quartile with an application in biological sciences

This manuscript builds on a novel, automatic, freely-available Bayesian approach to extract information in abstracts and titles to classify research topics by quartile. This approach is demonstrated for all N= 149,129 ISI-indexed publications in biological sciences journals during 2017. A Bayesian multinomial inverse regression approach is used to extract rankings of topics without the need of a pre-defined dictionary. Bigrams are used for extraction of research topics across manuscripts, and rankings of research topics are constructed by quartile. Worldwide and local results (e.g., comparison between two peer/aspirational research institutions in Colombia) are provided, and differences are explored both at the global and local levels. Some topics persist across quartiles, while the relevance of others is quartile-specific. Challenges in sustainable development appear as more prevalent in top quartile journals across institutions, while the two Colombian institutions favour plant and microorganism research. This approach can reduce information inequities, by allowing young/incipient researchers in biological sciences, especially within lower income countries or universities with limited resources, to freely assess the state of the literature and the relative likelihood of publication in higher impact journals by research topic. This can also serve institutions of higher education to identify missing research topics and areas of competitive advantage.

Flimma: a federated and privacy-aware tool for differential gene expression analysis

Aggregating transcriptomics data across hospitals can increase sensitivity and robustness of differential expression analyses, yielding deeper clinical insights. As data exchange is often restricted by privacy legislation, meta-analyses are frequently employed to pool local results. However, the accuracy might drop if class labels are inhomogeneously distributed among cohorts. Flimma (https://exbio.wzw.tum.de/flimma/) addresses this issue by implementing the state-of-the-art workflow limma voom in a federated manner, i.e., patient data never leaves its source site. Flimma results are identical to those generated by limma voom on aggregated datasets even in imbalanced scenarios where meta-analysis approaches fail.

Structural analysis of steel-concrete composite beam bridges utilizing the shear connection model

Shear connector (typically shear studs) plays a vital role as a transfer zone between steel and concrete in steel-concrete composite bridge girder. In the previous studies, the connection between steel beam and reinforced concrete slab were considered as continuous joint. However, in practice, this connection is discrete, which allows the slipping and peeling phenomenon between two layers (the influence of peeling is usually very small and could be ignored). To reflect this actual working mechanism, this study proposed a model of shear connection in the form of discrete points at the actual positions of studs for structural analysis. The model was simulated utilizing Timoshenko beam theory considering transverse shear effects. The numerical applications are carried out in order to compare two types of connections. The obtained results indicated that the proposed model properly reflected the actual performance of the structure and in some necessary cases, we should consider discrete connection for more accurate local results.

USING TAILORED GRAPHICAL TOOLS TO IMPROVE THE QUALITY OF DISPLACEMENT MAPS AT CTTC: THE VETOOLS

The Geomatics Division of the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) has been producing terrain displacement maps for more than 15 years using the PSIG software chain, developed entirely by the members of the aforesaid group. PSIG has reached a high level of maturity, being highly automated but also offering the user the possibility to fine-tune the set of critical parameters controlling the process. However, large areas with a high level of diversity often pose problems in finding a good quality solution using a single set of parameters. Improving the quality of the final terrain displacement map means being able to process very local and critical areas using specific sets of parameters; however, identifying such areas is a difficult process without suitable analysis tools. The VETools, a new software project still under development, but very close to its completion, target this problem. With the VETools it is possible to visualize the results produced by a previous PSIG global processing, analysing their quality, thus making possible to identify the local, critical areas, allowing the user to interactively experiment with specific sets of parameters for these areas, reprocessing them and reviewing the local results as many times as desired and, finally, merging all of them in a single, unique solution whose level of quality is appropriate for the whole area of interest. This work presents the current state of development of the VETools, describing their features and the challenges overcome.

Ball Convergence of a Parametric Efficient Family of Iterative Methods for Solving Nonlinear Equations

The goal is to extend the applicability of Newton-Traub-like methods in cases not covered in earlier articles requiring the usage of derivatives up to order seven that do not appear in the methods. The price we pay by using conditions on the first derivative that actually appear in the method is that we show only linear convergence. To find the convergence order is not our intention, however, since this is already known in the case where the spaces coincide with the multidimensional Euclidean space. Note that the order is rediscovered by using ACOC or COC, which require only the first derivative. Moreover, in earlier studies using Taylor series, no computable error distances were available based on generalized Lipschitz conditions. Therefore, we do not know, for example, in advance, how many iterates are needed to achieve a predetermined error tolerance. Furthermore, no uniqueness of the solution results is available in the aforementioned studies, but we also provide such results. Our technique can be used to extend the applicability of other methods in an analogous way, since it is so general. Finally note that local results of this type are important, since they demonstrate the difficulty in choosing initial points. Our approach also extends the applicability of this family of methods from the multi-dimensional Euclidean to the more general Banach space case. Numerical examples complement the theoretical results.

Quantitative Verification of Stochastic Regular Expressions

In this article, we introduce a probabilistic verification algorithm for stochastic regular expressions over a probabilistic extension of the Action based Computation Tree Logic (ACTL*). The main results include a novel model checking algorithm and a semantics on the probabilistic action logic for stochastic regular expressions (SREs). Specific to our model checking algorithm is that SREs are defined via local probabilistic functions. Such functions are beneficial since they enable to verify properties locally for sub-components. This ability provides a flexibility to reuse the local results for the global verification of the system; hence, the framework can be used for iterative verification. We demonstrate how to model a system with an SRE and how to verify it with the probabilistic action based logic and present a preliminary performance evaluation with respect to the execution time of the reachability algorithm.

Characterizing Stress Orientations in Southern Kansas

ABSTRACT Induced seismicity predominantly occurs along faults that are optimally oriented to the local principal compressive stress direction, and the characterization of these stress orientations is an important component of understanding seismic hazards. The seismicity rate in southern Kansas rapidly increased in 2013 primarily due to the disposal of large volumes of wastewater into the Arbuckle Group. Previously, local stress orientations in this area were poorly constrained, which limited our understanding of the complex faulting and diverse earthquake mechanisms in this region. We use shear-wave splitting and focal mechanism inversion techniques to create multiple, independent estimates of maximum horizontal stress directions (SHmax) and their spatial variation across the study area. We then create an integrated model of stress orientations for southern Kansas and northern Oklahoma using our local results in conjunction with previous, regional stress orientation estimates. We find that SHmax in both southern Kansas and central Oklahoma exhibits an east-northeast (∼N78° E) orientation, and these regions bound a northeast (∼N59° E) rotation within a ∼20 km area in northern Oklahoma near the Nemaha ridge.

Effect of the 3rd Dimension within the Representative Volume Element (RVE) on Damage Initiation and Propagation during Full-Phase Numerical Simulations of Single and Multi-Phase Steels

In this research, the effect of 2D and 3D Representative Volume Element (RVE) on the ductile damage behavior in single-phase (only ferrite) and dual-phase (ferrite and martensite) steels is analyzed. Physical and fitting parameters of the constitutive model for bcc-ferrite and bcc-martensite phases are adapted from the already published work. Crystal plasticity (CP) based numerical simulations without damage consideration are run and, later, ductile damage criteria for the ferrite phase is defined for all cases. The results of the non-damage (-nD-) and damage (-D-) simulations are compared to analyze the global and local differences of evolving stresses and strains. It is observed that for the same model parameters defined in all cases, damage initiation occurs at the overall higher global strain in the case of 3D compared to 2D. Based on statistical data analysis, a systematic comparison of local results is carried out to conclude that the 3D RVEs provide better quantitative and qualitative results and should be considered for such full phase simulations. Whereas 2D RVEs are simple to analyze and provide appropriate qualitative information about the damage initiation sites.

Improvement of Adequacy of Empirical Antimicrobial Therapy in Escherichia coli Bacteremia of Urinary Source in Catalonia (VINCat-PROA)

Background: The antibiotic use optimization program (PROA) in Catalonia (Spain) is part of the surveillance program for nosocomial infections in hospitals in Catalonia (VINCat). Despite the existence of guidelines for the treatment of urinary tract infections in hospitals, adherence to them is not guaranteed. Objective: Our objective was to evaluate the adequacy of empirical antimicrobial therapy to local guidelines in bacteremia caused by Escherichia coli of urinary source within the PROA-VINCat program during a 3-year period. The impact of a voluntary survey asking for evaluating local results and implementing correction measures was also analyzed. Methods: Multicentric prospective observational study including all episodes of E. coli bacteremia of urinary source between May 2017 and September 2019, in adult hospitalized patients in 45 Catalan hospitals. Adequacy of the empirical therapy to local guidelines was one of the prospectively recorded items. A survey evaluating local results of 2017–2018 and asking for possible correcting measures was sent to the participating centers at the end of 2018. Percentages of adequacy of empirical antimicrobial therapy in 2017, 2018, and 2019 were compared by means of χ2 test. Results: Overall, 3,804 episodes of bacteremia were recorded: 845 in 2017, 1,861 in 2018 and 1,098 until September 30, 2019. Globally, adequacy of empirical therapy to guidelines increased from 73.7% in 2017 to 78.2% in 2019 (P = .06). Interestingly, in the 24 hospitals that responded to the voluntary survey, the adequacy of empirical therapy increased significantly from 72.9% in 2017 to 79.9% in 2019 (P = .009). In hospitals that did not respond, adequacy remained the same over the years (76.7% in 2017, 75.1% in 2019; P = .90). Correction measures applied were: meeting with the antimicrobial stewardship team to evaluate the results (100%), review of local resistance rates (62%), review of local guidelines (58.3%), improving guidelines dissemination (75%), sessions for improving guidelines adherence (58%), and analysis of adherence to guidelines after education (65%). Conclusions: In the empirical treatment of E. coli bacteremia of urinary source, adequacy to local antimicrobial therapy guidelines improved from 2017 to 2019, but only in hospitals answering a voluntary survey regarding correcting measures for improving adequacy. Adherence to antimicrobial stewardship proposals improves indicators at local and regional level.Funding: NoneDisclosures: Juan Pablo Horcajada reports consulting fees from MSD, Pfizer, and Menarini and speaker honoraria from MSD, Pfizer, and Zambon.

An Intelligent Planning-Based Modeling Method for Diagnosis and Repair

Planning and model-based diagnosis are both branches of artificial intelligence. In model-based diagnosis, multiresults may be gotten which lead to an uncertain diagnosis. We use the landmark method from planning to designing an event sequence to get a reaction. A method that uses planning to repair in local results of incremental diagnosis is proposed. Firstly, a model is established on model-based diagnosis and planning. Incremental diagnosis results are used as the initial state of planning, and the heuristic search method is used to find the solution to an unfaulty state. Two algorithms with different strategies are designed for diagnosis and repair: one is to repair all possible faults and use controllable events to repair them, and the other is to test through the feedback of controllable events and observable events to get the only solution and repair them. At the same time, the efficiency of the incremental diagnosis method is improved based on heuristics.