SUMMARY
We study the initiation and growth of a dry granular shear zone subjected to seismic shearing and flash heating from the perspective of a discrete element method. For this purpose, we created ...a semi-periodic numerical shear test similar to a rotary shear machine in which a 2 mm ×1.5 mm sample composed of micrometric cohesive disks is sheared in between two rigid walls. The strength of cohesive bonds is defined according to an elasto-brittle contact law calibrated to simulate peak and residual strength envelopes derived from rock mechanics tests. The sample is traversed by a pre-existing fracture and subjected to a vertical confining pressure (e.g. 112.5 MPa) and a velocity step function (e.g. 1 m s–1) applied on the top and bottom walls, respectively. Slip along the fracture induces the growth of a shear zone, which thickens by progressive abrasion of damaged material from cohesive blocks. We carried out two parametric studies to determine the rheology and physical properties of the shear zone for slip velocities and confining pressures characteristic of shallow earthquakes and several flash-heating temperatures. According to parametric studies, the mechanical behavior of the shear zone exhibits three distinct phases. The initial phase of rupture initiation is characterized by the propagation of a shear instability generated by the velocity step (phase 1). During this phase, friction and dilatancy curves are approximated by asymmetric peak functions whose amplitude and geometry are controlled primarily by confining pressure. In the intermediate phase of shear-zone growth, the sample displays an initial transient stage that asymptotically approaches steady state at submelting temperatures (phase 2). According to the inertial number, seismic shearing occurs under quasi-static conditions despite high shear rates. Thus, friction and dilatancy observed in all simulations are roughly constant regardless of slip velocity, confining pressure, and gouge zone thickness. In the final phase of shear weakening, the model evolves toward a new steady state at flash-heating temperatures (phase 3). Average friction and dilatancy are represented by sigmoidal decreasing curves that approach steady-state values lower than for phase 2. Predictably, the thermally weakened friction in steady state (μss ∼ 0.1) is close to the strength of frictionless granular samples sheared in quasi-static conditions. We calculate breakdown energies for the gouge and damage zones and the fracture energy at intermediate and high confining pressures. We show that breakdown energy fundamentally differs from fracture energy commonly used in seismology. The breakdown energy of the damage zones shows long-period damped oscillations weakly correlated with shear-stress fluctuations around average decaying values. Our results suggest that dilatancy is the primary energy sink within the damage zones at steady-state values. The breakdown energy components of the gouge zone follow a similar decaying trend as the average fracture energy but over a longer critical distance. Decohesion and dilatancy are the major energy sinks linked to gouge formation at intermediate pressures. In contrast, dilatancy and debonding frictional energies predominate at high confining pressures. Breakdown energy is equivalent to a fraction of fracture energy that nearly triples when doubling the confining pressure.
Design Smells are indicators of situations that negatively affect software quality attributes such as understandability, testability, extensibility, reusability, and maintainability in general. ...Improving maintainability is one of the cornerstones of making software evolution easier. Hence, Design Smell Detection is important in helping developers when making decisions that can improve software evolution processes. After a long period of research, it is important to organize the knowledge produced so far and to identify current challenges and future trends. In this paper, we analyze 18 years of research into Design Smell Detection. There is a wide variety of terms that have been used in the literature to describe concepts which are similar to what we have defined as “Design Smells,” such as design defect, design flaw, anomaly, pitfall, antipattern, and disharmony. The aim of this paper is to analyze all these terms and include them in the study. We have used the standard systematic literature review method based on a comprehensive set of 395 articles published in different proceedings, journals, and book chapters. We present the results in different dimensions of Design Smell Detection, such as the type or scope of smell, detection approaches, tools, applied techniques, validation evidence, type of artifact in which the smell is detected, resources used in evaluation, supported languages, and relation between detected smells and software quality attributes according to a quality model. The main contributions of this paper are, on the one hand, the application of domain modeling techniques to obtain a conceptual model that allows the organization of the knowledge on Design Smell Detection and a collaborative web application built on that knowledge and, on the other, finding how tendencies have moved across different kinds of smell detection, as well as different approaches and techniques. Key findings for future trends include the fact that all automatic detection tools described in the literature identify Design Smells as a binary decision (having the smell or not), which is an opportunity to evolve to fuzzy and prioritized decisions. We also find that there is a lack of human experts and benchmark validation processes, as well as demonstrating that Design Smell Detection positively influences quality attributes.
Design smell detection has proven to be a significant activity that has an aim of not only enhancing the software quality but also increasing its life cycle.
This work investigates whether machine ...learning approaches can effectively be leveraged for software design smell detection. Additionally, this paper provides a comparatively study, focused on using balanced datasets, where it checks if avoiding dataset balancing can be of any influence on the accuracy and behavior during design smell detection.
A set of experiments have been conducted-using 28 Machine Learning classifiers aimed at detecting God classes. This experiment was conducted using a dataset formed from 12,587 classes of 24 software systems, in which 1,958 classes were manually validated.
Ultimately, most classifiers obtained high performances,-with Cat Boost showing a higher performance. Also, it is evident from the experiments conducted that data balancing does not have any significant influence on the accuracy of detection. This reinforces the application of machine learning in real scenarios where the data is usually imbalanced by the inherent nature of design smells.
Machine learning approaches can effectively be used as a leverage for God class detection. While in this paper we have employed SMOTE technique for data balancing, it is worth noting that there exist other methods of data balancing and with other design smells. Furthermore, it is also important to note that application of those other methods may improve the results, in our experiments SMOTE did not improve God class detection.
The results are not fully generalizable because only one design smell is studied with projects developed in a single programming language, and only one balancing technique is used to compare with the imbalanced case. But these results are promising for the application in real design smells detection scenarios as mentioned above and the focus on other measures, such as Kappa, ROC, and MCC, have been used in the assessment of the classifier behavior.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Summary
The COVID‐19 pandemic required people to confine themselves to their homes where possible, and disrupted normal hospital activities. We examine whether this lockdown generated changes in the ...size of the tumours. We compared the dimensions of the surgically removed malignant skin tumours from the first 150 patients treated after the confinement ended in Spain (22 May 2020) with those of the last 150 patients to receive such treatment before the confinement began (13 March 2020). Data on tumour surface area were collected from pathology reports. Overall, no significant difference was seen in the tumour sizes. However, among men, the tumours removed after confinement were significantly larger (P < 0.05). Controversy exists over how the reduction in the number of tumours diagnosed during lockdowns might have influenced the characteristics of tumours. In this study, no overall difference was seen in the size of the tumours removed, although those removed from men after confinement were larger.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
En este trabajo se realizó un análisis bibliométrico de los 69 años de publicaciones de Lilloa, para lo cual se revisaron un total de 774 trabajos y se consideraron 6 indicadores: producción total ...por año, tipo de publicación, disciplina, tipo de autores, lugares de trabajo y sexo de los autores. Esta contribución representa una síntesis de la historia de publicaciones de la revista y constituye un aporte orientador para el desarrollo y continuidad de la producción científica. Asimismo, esta revisión permitió observar la variabilidad a lo largo del tiempo y el crecimiento en calidad, cantidad y dedicación de los artículos.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
7.
Keystone flap used on the legs: case series Colorado Cogolludo, L.; Conde‐Taboada, A.; González‐Guerra, E. ...
Clinical and experimental dermatology,
August 2019, 2019-Aug, 2019-08-00, 20190801, Volume:
44, Issue:
6
Journal Article
Peer reviewed
Click here for the corresponding questions to this CME article.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
In recent years, glycosiltransferases have arisen as standard biocatalysts for the enzymatic synthesis of a wide variety of natural and non-natural nucleosides. Such enzymatic synthesis of nucleoside ...analogs catalyzed by nucleoside phosphorylases and 2′-deoxyribosyltransferases (NDTs) has demonstrated to be an efficient alternative to the traditional multistep chemical methods, since chemical glycosylation reactions include several protection–deprotection steps. This minireview exhaustively covers literature reports on this topic with the final aim of presenting NDTs as an efficient option to nucleoside phosphorylases for the synthesis of natural and non-natural nucleosides. Detailed comments about structure and catalytic mechanism of described NDTs, as well as their possible biological role, substrate specificity, and advances in detection of new enzyme specificities towards different non-natural nucleoside synthesis are included. In addition, optimization of enzymatic transglycosylation reactions and their application in the synthesis of natural and non-natural nucleosides have been described. Finally, immobilization of NDTs is shown as a practical procedure which leads to the preparation of very interesting biocatalysts applicable to industrial nucleoside synthesis.
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CEKLJ, DOBA, EMUNI, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK
New and previous fossil remains and resulting biostratigraphy of the El Imperial Formation at Arroyo del Imperial, Quebrada de La Horqueta, and Cañón del Atuel key sections are analyzed, while the ...faunal relationships among them are clarified. Two diachronnous faunas, the pTS and TSAIII associations, relatives to the Tivertonia-Streptorhynchus assemblage are recognized and constrained to early late Bashkirian and Moscovian ages, respectively. These age assignments are supported by statistical analyses and available palynological and radiometric dating. Previous mentions of brachiopods from Arroyo del Imperial and Quebrada de La Horqueta are elucidated with the identification of Buxtonia cf. riojanae (Leanza), Streptorhynchus inaequiornatus Leanza, Spiriferellina? sp., Septosyringothyris (Precosyringothyris) aff. jaguelensis Lech, Septosyringothyris (Precosyringothyris) cf. feruglioi (Amos), Saltospirifer guevarai Cisterna and Archbold and Pericospira sp. A new marine fauna from the upper part of the Cañón del Atuel section (Cabecera del Cañón Member) is reported. It includes the brachiopods Argentiella cf. A. stappenbecki Archbold, Cisterna and Sterren, Oehlertella annae (Feruglio), Orbiculoidea saltensis Reed, Calytrixia piersoni Taboada, Coolkilella aredesi Taboada, Costatumulus sp. and Septosyringothyris? sp. A bio-chronostratigraphic correlation scheme, including key lithostratigraphic units and biozones of central-western Argentina is updated.
•Previous and new brachiopod records from the San Rafael Basin are identified and elucidated.•Two diachronic faunas of the El Imperial Formation, relatives to the Tivertonia-Streptorhynchus faunal assemblage, are distinguished and discussed.•Intrabasinal bio-chronological correlation among different sections of El Imperial Formation is clarified.•A bio-chronostratigraphic correlation scheme of lithostratigraphic units and biozones of central-western Argentina is updated.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Design smell detection has proven to be an efficient strategy to improve software quality and consequently decrease maintainability expenses. This work explores the influence of the information ...about project context expressed as project domain and size category information, on the automatic detection of the
god class
design smell by machine learning techniques. A set of experiments using eight classifiers to detect
god classes
was conducted on a dataset containing 12, 587 classes from 24 Java projects. The results show that classifiers change their behavior when they are used on datasets that differ in these kinds of project information. The results show that
god class
design smell detection can be improved by feeding machine learning classifiers with this project context information.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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