bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stress-Dependent Deformation and Permeability of a Fractured Coal Subject to Excavation-Related Loading Paths
Authors: Cao Wenzhuo , Lei Qinghua , Cai Wu 
Published: June 2021

AbstractThe deformation and permeability of coal are largely affected by the presence and distribution of natural fractures such as cleats and bedding planes with orthogonal and abutting characteristics, resulting in distinct hydromechanical responses to stress loading during coal mining processes. In this research, a two-dimensional (2D) fracture network is constructed based on a real coal cleat trace data collected from the Fukang mine area, China. Realistic multi-stage stress loading is designed to sequentially mimic an initial equilibrium phase and a mining-induced perturbation phase involving an increase of axial stress and a decrease of confining stress. The geomechanical and hydrological behaviour of the fractured coal under various stress loading conditions is modelled using a finite element model, which can simulate the deformation of coal matrix, the shearing and dilatancy of coal cleats, the variation of cleat aperture induced by combined effects of closure/opening, and shear and tensile-induced damage. The influence of different excavation stress paths and directions of mining is further investigated. The simulation results illustrate correlated variations among the shear-induced cleat dilation, damage in coal matrix, and equivalent permeability of the fractured coal. Model results are compared with results of previous work based on conventional approaches in which natural fracture networks are not explicitly represented. In particular, the numerical model reproduces the evolution of equivalent permeability under the competing influence of the effective stress perpendicular to cleats and shear-induced cleat dilation and associated damage. Model results also indicate that coal mining at low stress rates is conducive to the stability of surrounding coal seams, and that coal mining in parallel to cleat directions is desirable. The research findings of this paper have important implications for efficient and safe exploitation of coal and coalbed methane resources.
Proline oxidase silencing inhibits p53-dependent apoptosis in MCF-7 breast cancer cells
Authors: Oscilowska Ilona , Huynh Thi Y. L. , Baszanowska Weronika , Prokop Izabela , Surazynski Arkadiusz , Galli Mauro , Zabielski Piotr , Palka Jerzy 
Published: June 2021

AbstractProline oxidase (POX) is mitochondrial proline-degrading enzyme of dual apoptosis/survival function. POX expression and proline availability are considered an underlying mechanism for differential POX functions. The mechanism for POX-dependent regulation of cell death/survival was studied in wild-type (MCF-7WT) and shRNA POX-silenced breast cancer cells (MCF-7iPOX). Proline concentration and proteomic analyses were determined by LC/MS/QTOF and LC/MS/ORBITRA, respectively. Inhibition of collagen biosynthesis (proline utilizing process) by 2-methoxyestradiol (2ME) contributed to induction of apoptosis in MCF-7WT cells, as detected by increase in the expression of active caspase-3, -9 and p53. The process was not shown in MCF-7iPOX. In MCF-7iPOX cells prolidase activity and expression as well as proline concentration were drastically increased, compared to MCF-7WT cells. Down-regulation of p53 in MCF-7iPOX cells was corroborated by proteomic analysis showing decrease in the expression of p53-related proteins. The mechanism for down-regulation of p53 expression in MCF-7iPOX cells was found at the level of p53–PEPD complex formation that was counteracted by hydrogen peroxide treatment. In this study, we found that silencing POX modulate pro-survival phenotype of MCF-7 cells and suggest that the mechanism of this process undergoes through down-regulation of p53-dependent signaling.
Effect of tolvaptan in Japanese patients with autosomal dominant polycystic kidney disease: a post hoc analysis of TEMPO 3:4 and TEMPO Extension Japan
Authors: Muto Satoru , Okada Tadashi , Shibasaki Yoshiyuki , Ibuki Tatsuki , Horie Shigeo 
Published: June 2021

Abstract
Background
Autosomal dominant polycystic kidney disease (ADPKD) is a progressive condition that eventually leads to end-stage renal disease. A phase 3 trial of tolvaptan (TEMPO 3:4; NCT00428948) and its open-label extension (TEMPO Extension Japan: TEMPO-EXTJ; NCT01280721) were conducted in patients with ADPKD. In this post hoc analysis, effects on renal function and the safety profile of tolvaptan were assessed over a long-term period that included the 3-year TEMPO 3:4 and the approximately 3-year TEMPO-EXTJ trials.

Methods
Patients from Japanese trial sites who completed TEMPO 3:4 were offered participation in TEMPO-EXTJ. Patients whose efficacy parameters were measured at year 2 in TEMPO-EXTJ for efficacy evaluation were included. The annual slope of the estimated glomerular filtration rate (eGFR) and growth in total kidney volume (TKV) were analyzed.

Results
In patients who received tolvaptan in TEMPO 3:4 and TEMPO-EXTJ, the annual slope of eGFR (mL/min/1.73 m2) was − 3.480 in TEMPO 3:4 and − 3.417 in TEMPO-EXTJ, with no apparent effect of an approximately 3.6-month off-treatment interval between the two trials. In patients who received a placebo in TEMPO 3:4 before initiating tolvaptan in TEMPO-EXTJ, the slope of eGFR was significantly less steep from TEMPO 3:4 (− 4.287) to TEMPO-EXTJ (− 3.364), a difference of 0.923 (P = 0.0441).

Conclusion
The TEMPO-EXTJ trial supports a sustained beneficial effect of tolvaptan on eGFR. In patients who received a placebo in TEMPO 3:4, initiation of tolvaptan in TEMPO-EXTJ was associated with a significant slowing of eGFR decline.
Effect of non-native species on taxonomic and functional diversity of fish communities in different river types
Authors: Takács Péter , Abonyi András , Bánó Bálint , Erős Tibor 
Published: June 2021

AbstractRecent researches suggest that functional diversity represents the response of communities to environmental alterations better than taxonomic diversity. However, there is scarce information about how the functional diversity of freshwater fishes is affected by habitat type and the dominance of non-native species. To address this question, we analysed a large database containing 15 morpho-functional traits of 61 fish species from the Pannon Biogeographic region (Hungary). Based on a fish faunistic list and relative abundance of taxa, we quantified the taxonomic and functional diversity of riverine communities for > 700 sites of six habitat types. We asked how non-native fishes affected the taxonomic and functional diversity in different river types and at the local scale (i.e. at the site level), and how the diversity measures of native fauna elements changes along the invasion gradient. Our results showed that both functional and taxonomic richness increases with habitat complexity, from small headwater streams to large rivers. Therefore taxonomic diversity served as a good proxy for functional diversity along the environmental gradient of river types. Non-natives showed considerable functional diversity relative to their species number in each habitat type. Diversity values of native fauna elements initially increased, and then showed a major decrease along the invasion gradient. River type-specific evaluations highlighted the importance of considering the proliferation of invasive species based on both taxonomic and functional diversity indices. We argue that type-specific action plans are needed in conservation management to preserve the taxonomic and functional diversity of native fishes in Hungary, but also elsewhere.
Thalamocortical Spectral Transmission Relies on Balanced Input Strengths
Authors: Saponati Matteo , Garcia-Ojalvo Jordi , Cataldo Enrico , Mazzoni Alberto 
Published: June 2021

AbstractThe thalamus is a key element of sensory transmission in the brain, as it gates and selects sensory streams through a modulation of its internal activity. A preponderant role in these functions is played by its internal activity in the alpha range ([8–14] Hz), but the mechanism underlying this process is not completely understood. In particular, how do thalamocortical connections convey stimulus driven information selectively over the back-ground of thalamic internally generated activity? Here we investigate this issue with a spiking network model of feedforward connectivity between thalamus and primary sensory cortex reproducing the local field potential of both areas. We found that in a feedforward network, thalamic oscillations in the alpha range do not entrain cortical activity for two reasons: (i) alpha range oscillations are weaker in neurons projecting to the cortex, (ii) the gamma resonance dynamics of cortical networks hampers oscillations over the 10–20 Hz range thus weakening alpha range oscillations. This latter mechanism depends on the balance of the strength of thalamocortical connections toward excitatory and inhibitory neurons in the cortex. Our results highlight the relevance of corticothalamic feedback to sustain alpha range oscillations and pave the way toward an integrated understanding of the sensory streams traveling between the periphery and the cortex.
Usefulness of a multiparametric evaluation including global longitudinal strain for an early diagnosis of acute myocarditis
Authors: Degiovanni Anna , Pastore Maria Concetta , Spinoni Enrico Guido , Focardi Marta , Cameli Matteo , Patti Giuseppe 
Published: June 2021

AbstractCardiac magnetic resonance imaging (CMRI) represents the main imaging modality for diagnosing acute myocarditis. However, its limited availability could entail missing or delayed diagnosis. A reduction of left ventricular global longitudinal strain (LV GLS) by speckle tracking echocardiography (STE) correlates with amount of oedema in acute myocarditis and here may be early detected. Aim was to evaluate the diagnostic and prognostic role of 3-layers LV GLS in patients with acute myocarditis. Out of 122 patients with suspected acute myocarditis, a total of 86 consecutive patients with CMRI-confirmed acute myocarditis admitted in two Italian institutions were retrospectively screened. Exclusion criteria were met in 29 patients because of poor acoustic window or missing data. A total of 57 patients were then included. Clinical characteristics, laboratory examinations, transthoracic echocardiography data and STE parameters were collected early after hospitalization. In the study population, mean age was 38.8 ± 15.6 years, the prevalence of male gender was 90%. On admission, 22 patients (39%) had fever (body temperature > 37.5 °), mean white blood cell (WBC) count was 10.9 ± 1.7/10^3 and overall LV ejection fraction was 50.1% ± 11.2. An epicardial LV GLS < 18% was present in 74% of patients, and a model including at least one of LV GLS < 18% (absolute value), fever and WBC > 10.0/10^3 was able to identify all patients with CMRI-diagnosed acute myocarditis. An epicardial LV GLS < 15.3% (absolute value) at baseline significantly predicted the lack of myocarditis resolution during follow-up (AUC 0.76, 95% CI 0.58–0.93, p = 0.02). A multiparametric model including epicardial LV GLS, fever and elevated WBC count on admission could be useful for early diagnosing an acute myocarditis, especially when CMRI is not promptly available. Baseline epicardial LV GLS may also identify patients with less-likely myocarditis resolution.
Smart sheet metal forming: importance of data acquisition, preprocessing and transformation on the performance of a multiclass support vector machine for predicting wear states during blanking
Authors: Kubik Christian , Knauer Sebastian Michael , Groche Peter 
Published: June 2021

AbstractIn consequence of high cost pressure and the progressive globalization of markets, blanking, which represents the most economical process in the value chain of manufacturing companies, is particularly dependent on reducing machine downtimes and increasing the degree of utilization. For this purpose, it is necessary to be able to make a real-time prediction about the current and future process conditions even at high production rates. Therefore, this study investigates the influence of data acquisition, preprocessing and transformation on the performance of a multiclass support vector machine to classify abrasive wear states during blanking based on force signals. The performance of the model was quantitatively evaluated based on the model accuracy and the separability of the classes. As a result, it was shown, that the deviation of time series represents the key parameter for the resulting performance of the classification model and strongly depends on the sensor type and position, the preprocessing procedure as well as the feature extraction and selection. Furthermore, it is shown that the consideration of domain knowledge in the phases of data acquisition, preprocessing and transformation improves the performance of the classification model and is essential to successfully implement AI projects. Summarizing the findings of this study, trustworthy data sets play a crucial role for implementing an automated process monitoring as a basis for resilient manufacturing systems.
Formally-based Model-Driven Development of Collaborative Robotic Applications
Authors: Askarpour Mehrnoosh , Lestingi Livia , Longoni Samuele , Iannacci Niccolò , Rossi Matteo , Vicentini Federico 
Published: June 2021

AbstractThe development of Human Robot Collaborative (HRC) systems faces many challenges. First, HRC systems should be adaptable and re-configurable to support fast production changes. However, in the development of HRC applications safety considerations are of paramount importance, as much as classical activities such as task programming and deployment. Hence, the reconfiguration and reprogramming of executing tasks might be necessary also to fulfill the desired safety requirements. Model-based software engineering is a suitable means for agile task programming and reconfiguration. We propose a model-based design-to-deployment toolchain that simplifies the routine of updating or modifying tasks. This toolchain relies on (i) UML profiles for quick model design, (ii) formal verification for exhaustive search for unsafe situations (caused by intended or unintended human behavior) within the model, and (iii) trans-coding tools for automating the development process. The toolchain has been evaluated on a few realistic case studies. In this paper, we show a couple of them to illustrate the applicability of the approach.
Transporting Deformations of Face Emotions in the Shape Spaces: A Comparison of Different Approaches
Authors: Piras Paolo , Varano Valerio , Louis Maxime , Profico Antonio , Durrleman Stanley , Charlier Benjamin , Milicchio Franco , Teresi Luciano 
Published: June 2021

AbstractStudying the changes of shape is a common concern in many scientific fields. We address here two problems: (1) quantifying the deformation between two given shapes and (2) transporting this deformation to morph a third shape. These operations can be done with or without point correspondence, depending on the availability of a surface matching algorithm, and on the type of mathematical procedure adopted. In computer vision, the re-targeting of emotions mapped on faces is a common application. We contrast here four different methods used for transporting the deformation toward a target once it was estimated upon the matching of two shapes. These methods come from very different fields such as computational anatomy, computer vision and biology. We used the large diffeomorphic deformation metric mapping and thin plate spline, in order to estimate deformations in a deformational trajectory of a human face experiencing different emotions. Then we use naive transport (NT), linear shift (LS), direct transport (DT) and fanning scheme (FS) to transport the estimated deformations toward four alien faces constituted by 240 homologous points and identifying a triangulation structure of 416 triangles. We used both local and global criteria for evaluating the performance of the 4 methods, e.g., the maintenance of the original deformation. We found DT, LS and FS very effective in recovering the original deformation while NT fails under several aspects in transporting the shape change. As the best method may differ depending on the application, we recommend carefully testing different methods in order to choose the best one for any specific application.
Trends of out-mobility from large housing estates in Stockholm: influences of the housing policy and neighbourhood context
Authors: Kadarik Kati , Kährik Anneli 
Published: June 2021

AbstractSince 1990s Stockholm housing market has seen deregulations in accordance with liberalization trends in other European welfare states. The new governance principles together with increasing immigration and public rental housing conversions into cooperative housing in attractive inner city areas have put pressure on still rental-dominated estates because fewer rental dwellings must now cater to expanding numbers of people who have little choice on the housing market. In recent decades, many estates have displayed increasing signs of stigmatization, social exclusion, and outflow of relatively affluent people. This paper improves our knowledge of how the housing policy and economic changes have affected out-mobility from the housing estates in case of three cohorts of young people and how the childhood neighbourhood conditions affect this. Individual annual Swedish registry data (1990–2014) are employed to longitudinally study the out-mobility patterns of three cohorts that grew up in the estates against the backdrop of marketization, growing inequality and deteriorating conditions. This study supplements the existing literature on housing estates by clarifying how income has become more and ethnicity less important over time in explaining sorting patterns from these estates. However, the combination of the two has determined sorting throughout the study period. Growing up in a higher socioeconomic status neighbourhood had modest impact on reducing socioeconomic differences in out-mobility from the estates, while leading to more sorting based on ethnic background.
A New Generalized Variance Approach for Measuring Multidimensional Inequality and Poverty
Authors: Hajdu Ottó 
Published: June 2021

AbstractThe paper suggests a new generalized variance concept for measuring multidimensional inequality of a stratified society, based on multivariate statistical methods, where the members of society form a cloud in the oblique space of dimensions of inequality, such as income, expenditure and property. The cloud presents the multidimensional inequality capsulized in the cloud. The goal is to condense all the inequality information embodied by the cloud into a composite compact metric characterizing both the shape and the inner structure of the cloud. Contrary to the conventional literature that considers multidimensionality as a unidimensional weighted combination of the dimensions, our new composite index measures the inequality of the configuration of the points in the cloud. Our aim is twofold. First, we introduce the Inequality Covariance Matrix (ICM) assigned to the cloud, with elements measuring the correlations among dimensions. Having ICM, we propose the Generalized Variance (GV) of ICM to measure the composite Generalized Variance Inequality (GVI) level. Second, to evaluate the stratum-specific structure of the overall inequality, we suggest a new two-stage procedure. In the first stage, we divide the total GVI into between-groups and within-groups effects. Then, in the second stage the contributions of the strata to the within-groups inequality and, the contributions of the dimensions to the between-groups inequality are calculated. This GVI approach is sensitive to the correlation system, decomposable into stratum effects and, the number of dimensions is not limited. Moreover, including the log-dimensions in the analysis, GVI yields an Entropy Covariance Matrix giving a new Generalized Variance Entropy index. Finally, the GVI of censored poverty indicators means multidimensional poverty measurement. This special complex task is not yet solved in the traditional literature so far.
The key to the knowledge norm of action is ambiguity
Authors: Rich Patricia 
Published: June 2021

AbstractKnowledge-first epistemology includes a knowledge norm of action: roughly, act only on what you know. This norm has been criticized, especially from the perspective of so-called standard decision theory. Mueller and Ross provide example decision problems which seem to show that acting properly cannot require knowledge. I argue that this conclusion depends on applying a particular decision theory (namely, Savage-style Expected Utility Theory) which is ill-motivated in this context. Agents’ knowledge is often most plausibly formalized as an ambiguous epistemic state, and the theory of decision under ambiguity is then the appropriate modeling tool. I show how to model agents as acting rationally on the basis of their knowledge according to such a theory. I conclude that the tension between the knowledge norm of action and formal decision theory is illusory; the knowledge-first paradigm should be used to actively select the decision-theoretical tools that can best capture the knowledge-based decisions in any given situation.
Coordination in theory extension: how Reichenbach can help us understand endogenization in evolutionary biology
Authors: Luchetti Michele 
Published: June 2021

AbstractReichenbach’s early solution to the scientific problem of how abstract mathematical representations can successfully express real phenomena is rooted in his view of coordination. In this paper, I claim that a Reichenbach-inspired, ‘layered’ view of coordination provides us with an effective tool to systematically analyse some epistemic and conceptual intricacies resulting from a widespread theorising strategy in evolutionary biology, recently discussed by Okasha (2018) as ‘endogenization’. First, I argue that endogenization is a form of extension of natural selection theory that comprises three stages: quasi-axiomatisation, functional extension, and semantic extension. Then, I argue that the functional extension of one core principle of natural selection theory, namely, the principle of heritability, requires the semantic extension of the concept of inheritance. This is because the semantic extension of ‘inheritance’ is necessary to establish a novel form of coordination between the principle of heritability and the extended domain of phenomena that it is supposed to represent. Finally, I suggest that—despite the current lack of consensus on the right semantic extension of ‘inheritance’—we can fruitfully understand the reconceptualization of ‘inheritance’ provided by niche construction theorists as the result of a novel form of coordination.