Miracle-dz/UniFAR-FTUs huggingface dataset:
ENHANCING TIME-FREQUENCY REPRESENTATIONS FOR FAULT ANALYSIS IN GEARED SYSTEMS

The knowledgement of the fault development phenomenon in geared systems has been considered an important task not only in the design project but also in the maintenance of it. Usually, the vibration signal generated by these systems are multi-component signal and not stationary signal due to transient forces that appears from the superficial contact between the teeth and some type of imperfection, which is developed in the form of vibrations that excite several resonance frequencies of the system. The classic spectral analysis applied to the fault detection has shown limitations, especially concerning in the appearance of spurious components that can contaminate the spectrum and difficult the interpretation. To minimize these problems, this work investigates two time-frequency representations, which can supply a new discernment about the interpretation of these signals, evidencing the physical phenomenon caused by transient vibrations. The aim of this work is to establish some parameters that allow comparing, in the timefrequency representation, the Spectrogram and the Pseudo Wigner-Ville to apply in the fault analysis in gear systems and also to enhance the fault signal due to the residual signals. Some experimental tests, using three different conditions, are performed with these gear signals: toothless gear, scratched gear and normal gear. It was verified that the Pseudo Wigner-Ville technique is a powerful tool to analyze faults in geared systems.
TECHNIQUES FOR THE INTERACTIVE EXPLORATION OF HIGH-DETAIL 3D BUILDING RECONSTRUCTIONS USING THE EXAMPLE OF ROMAN COLOGNE

: This paper presents the results achieved by an interdisciplinary team of archaeologists, designers, and computer graphics engineers with the aim to virtually reconstruct an interactive high-detail 3D city model of Roman Cologne. We describe a content creation pipeline established to enable a flexible exchange and enhancement of building models, the applied optimization techniques necessary for real-time rendering, and the design of an application framework that enables the coupling of 3D visualizations with additional information in corresponding Adobe ® Flash ® widgets. Furthermore, we expose challenges arising by incorporating state-of-the-art visualization techniques, such as cut-away views, non-photorealistic rendering (NPR), and automated label placement. These techniques are used to enhance the interactive 3D environments, to enable for the presentation of interior structures, the precise communication what is hypothetic and what proven knowledge, and the integration of meta-information.
Inchworm Inspired Pneumatic Soft Robot Based on Friction Hysteresis

In this paper, we present an inchworm-inspired pneumatic soft robot that requires only one degree-of-freedom control to generate continuous linear locomotion on various surfaces. The locomotion is realized by the friction hysteresis resulting from the deformability of one robot leg, which is passively enabled by the robot design. The inchworm robot is made of a single material, has a single degree of freedom, and only requires the air pressure as a single-channel control signal to realize continuous locomotion.
The best bet: Should the new CEO acquire or divest?

This paper examines the M&A strategy of firms during the first year in office following the appointment of a new CEO and its effect on longer-term firm performance. Using a unique sample of large European listed companies, the results show that CEOs of UK firms execute more deals than their counterparts in France, Germany and Spain, which could be a reflection of both a more aggressive attitude to deal-making and differences in the legal environment in continental Europe. Furthermore, following poor financial performance in companies prior to their appointment, CEOs hired with a ‘mandate to change’, use deal-making as their strategic tool to restructure the firm, favouring divestiture. Firms with strong board power are also more likely to perform deals and favour divestitures over acquisitions in the first year of a new CEO’s tenure. Firms which mainly carry out divestitures as their deal-making strategy have a positive impact on their shortand medium-term performance during the first two years in office of a newly appointed CEO. As to the manner of the new appointment, forced and external succession is associated with performance improvement, as well as the strength of the board (using the level of institutional ownership as a proxy).
Characterization studies of Waste- bio-derived feedstocks

The WAVES project aims on exploring new and emerging technologies in heterogeneous catalysis towards the production of aviation and road transportation fuels (i.e., gasoline, kerosene, diesel) via hydroprocessing (hydro-isomerization, hydrocracking or hydrodeoxygenation) of waste and/or renewable bio-feedstocks (vegetable oil, F-T waxes, algae oil and bio-oil) via the development of new and selective catalysts with tuneable properties. In the present study biomass pyrolysis oil from 5 different biomass feedstocks, have been collected and characterized in CPERI (elemental analysis, gross calorific value, composition, acidity, bulk density and moisture, etc.), in view of elucidating how each feedstock’s varying properties matches the different needs for quality improvement upgrading towards fuel production. An in-depth characterization of the ‘major components’ in the bio-oil feeds were performed with a, hyphenated high resolution chromatographic techniques like GCxGC-ToFMS.
Advancing agroecology in Europe through a scenario exercise: a political and methodological framework

ww w. id dr i.o rg KEY MESSAGES Against this backdrop, this policy brief seeks to demonstrate the value added of a scenario exercise that explicitly describes possible transition pathways towards an agroecology transition in Europe to fuel the policy debate on European agriculture transformation. It proposes orientations on how to frame such and exercise from both a methodological and a political point of view: m 1. From a methodological point of view, we show the need for a scenario exercise to be multi-scalar and to integrate four perspectives: a. an agrarian system approach, linking agroecological transition processes at the landscape level to the evolution of global food supply at the European level; b. an analysis of the trends and drivers of change on the “consumption side”, and particularly possible and necessary changes in diets; c. a food chain perspective, which reflects upon how current trends in the food chain should be inflected to allow for technical and commercial changes at the farm level; d. an institutional perspective, which identifies how the European regulatory framework needs to be changed and what are the levers to remove socio-technical lock-in. m 2. From a political point of view, we demonstrate that to really open strategic opportunities, a scenario exercise should: a. not only describe a picture of the European agriculture converted to agroecology 20 years down the line but also narrate the pathway(s) through which such a transition could happen; b. compare an agro-ecological scenario to a business-as-usual (BAU) scenario to enable a wide and symmetrical discussion of potential costs and benefits of both scenarios, in particular the possible deadlocks of the BAU, that are often not explicitly discussed, as well as the whole range of benefits of an agroecological transition scenario, that are often disregarded. Advancing agroecology in Europe through a scenario exercise: a political and methodological framework
What to do with all these bits?

The claim here in is that we can store computational capacity for future generations to use in times of scarcity. The conjecture is that this capacity can be stored in systems through mechanisms related to exchanges of information and associated entropic gradients (and accompanying forces). In this paper we will describe the connections between the thermodynamics of the heat engine and the thermodynamics of information theory in order to postulate a structure through which computational capacity is stored for use in a computationally constrained future. The motivation for this conjecture is rooted in: well-understood and repurposed thermodynamic principles; significant advances in the understanding (via major improvements in data accusation) of complex ecosystems; newly emerging perspectives regarding the relationship between gravity and information exchange; and the need to create mechanistic solutions for problems rooted in complexity science (i.e. climate change.) An agenda of theoretical and empirical foundations is presented to serve as a guide for the discussion. It provides the context for deeper discussion of topics such as: the relationship between the emergence of thermodynamics and information theory with particular emphasis on the role of entropy; mathematical implementation of these concepts with respect to multi-continuum descriptions of systems and processes; and case studies to describe how this combination of new ideas can be implemented to understand and design complex systems. These case studies are specifically chosen to highlight the multi-scale multi-domain applicability of this unique approach to analysis and design of natural and engineered processes; and to suggest methods through which these systems store computational capacity.
A new measure of dissimilarity and fuzzy linear programming model to construct phylogenetic network among DNA sequences

The growth of DNA databases used to store large number of biological sequence data, has stimulated the importance of alignment of sequences for phylogenetics. Most of the phylogenetic methods based on alignment of sequences consume long time to provide the results. In this regard, a new alignment free measure, based on frequency of occurrence of different nucleotides in sequences has been reported. The Euclidean distance metric has been used over these frequencies of nucleotides to obtain the dissimilarities among DNA sequences. These distances are then used to construct the phylogenetic tree among sequences. In addition, a fuzzy linear programming model has been developed here to construct the phylogenetic network which is considered as the generalized form of phylogenetic tree. As an application, the proposed method is applied over the data set of  - globin gene of nine species and is validated by comparing the obtained results with the already existing method. The results obtained are more promising over the available method and can be applied over any length of input data sequences.
THE MISSING LINK BETWEEN CSR AWARDS

The aim of this paper is to address the conditions and mechanisms under which corporate responsibility (CR hereafter) awards may improve financial performance. Specifically, we argue that investor attention as measured by stock popularity is relevant for the relationship between CR awards and financial performance. Using a balanced panel of 879 firms from 25 countries over the 2005-2014 period, linear OLS regression first suggested that there is no significant relationship between CR awards and Tobin’s Q, even after controlling for investor attention. We went beyond this result and implemented a panel-threshold regression (PTR) analysis to study whether there is an optimal investor attention level which may result in threshold effect and asymmetrical responses of the financial performance to CR awards. Interestingly, empirical results show that returns on CR awards are either not significant or negative below the threshold but then become significantly positive above it. Our results remain robust under several different proxies, estimation methods and sample compositions. Overall, this study indicate that CR awards enhance financial performance indirectly through improved firm visibility, but only from a point at which investor attention is optimal.
Kawasaki Disease: Global Burden and Genetic Background

Kawasaki disease (KD) is a childhood vasculitides associated with serious coronary artery lesions. It is the most common cause of pediatric acquired heart disease in developed countries, and is increasingly reported from many rapidly industrializing developing countries. The incidence varies widely among different nations and is highest in North-East Asian countries, where almost 1 in 100 children in Japan having the disease by age of 5, where the lowest incidence reported in sub-Saharan Africa. The etiology of KD is still uncertain; interaction between a genetic predisposition and several environmental and immunological factors has been hypothesized. Several susceptibility genes were identified to be associated with the development of KD and increased risk of coronary artery lesions. Gene-gene associations and alteration of deoxyribonucleic acid (DNA) methylation are also found to play key roles in the pathogenesis and prognosis of KD. This article will focus on the global epidemiological patterns of KD, and the currently known genetic predisposition.
Multi-agent, case-based configuration of custom-built racing cars

The assembly of a custom-built automobile can be challenging, because of the multitude of car components that can be used and their configuration possibilities among one another. Several components are combined to create a car component, for example six parts are used to create a rear axle and several constraints have to be considered for a successful configuration. In this paper we present the work done within a masters thesis [19], namely a prototype of a multi-agent system for case-based configuration of car components, especially for creating new components by using preexisting components.
From the museum to the browser: Translating a music-driven exhibit from physical space to a web app

This paper describes the process of developing a browser-based version of GrooveMachine, a tangible museum exhibit that aims to foster interest in computer science (CS) through the music-driven exploration of a computational system. GrooveMachine is aimed at kids aged 10-14, and specifically targets learners from from groups currently under-represented in computing by demonstrating CS applications that challenge stereotypes. While an observational study suggests that GrooveMachine triggers situational interest, long-term engagement with CS requires this interest to be deepened and developed. To provide an opportunity for interest development, we have implemented a browser-based GrooveMachine. This not only oﬀers the opportunity for learners to continue their exploration of CS through creative interaction, but provides a pathway to other music and CS learning platforms where they can deepen this interest. In this paper we describe the theoretical underpinnings of interest, how it relates to CS, and how it intersects with identity. We also describe the diﬀerences between the museum and browser contexts. We detail the design and implementation of GrooveMachine in the museum and explain how we translated it to the browser, including the rationale behind our central design decisions and a discussion of our technical implementation. In this way we provide valuable insight for researchers who want to reach larger audiences by developing browser-based versions of physical installations.
An Effective Approach for Citation Intent Recognition Based on Bert and LightGBM

In the development of science and technology, the public scientific theses have played an important role and greatly promoted the development of society. The vast majority scientific progress was announced in the form of papers in past centuries, and impactful contributions were often recognized by the research community with a great number of citations. However, inappropriate citation of papers still occurs from time to time and hinders the progress of human civilization. In this paper, we proposed an effective framework to address the citation intent recognition challenge in ACM WSDM Cup 20201. Our team name is ferryman and in our solution, we regarded this problem as the Information Retrieve (IR) task and proposed a framework with two stages of recall and ranking and finally our team won the 1st place with a Mean Average Precision @ 3 (MAP@3) score of 0.42583 on the final leaderboard2.
Who Benefits from Public Education Provision? Evidence from Italy

Public education provision is redistributive when rich families, who contribute to its financing, find it optimal to sort out of the public system and buy the educational services on the private market. This may occur if the quality of the educational services is lower in the public sector than it is in the private. We estimate structural quantile treatment effects to analyze the mechanisms behind the redistributiveness of public education provision using Italian data. We exploit heterogeneity in expected tax deductions to exogenously manipulate the distribution of net of taxes income, equalized by families needs, and explore the consequences of this manipulation on various quantiles of the distribution of the amount of the educational transfers in kind. We find that an increase in income reduces the amount of educational transfers in-kind (i) more for higher quantiles of the educational transfers in-kind (ii) more for lower quantiles of the households’ earning capacity. Our findings explain how, for compulsory schooling, the households’ sorting into private education may motivate a government, that aims at redistributing resources from the rich to the poor, to use public education provision as transfers in-kind.
Recall and Re-rank: An Empirical Ensemble Framework for Citation Intent Recognition

With more and more new discoveries and theories being openly distributed and discussed in published articles, some unscrupulous behaviors of “coercive” citations have become regrettably prevalent, posing a threat to our scholar field. Thus, Microsoft holds the Citation Intent Recognition Challenge to encourage more people to pay attention to this issue. We treat the task as query-based passage re-ranking task which includes two stages of candidate passage recall and passage re-ranking. To resolve the task, we propose an empirical ensemble recall and re-rank framework for citation intent recognition which both takes full advantage of features and merits of various recall and re-ranking methods. Our entry achieves test set Mean Average Precision@3 (MAP@3) of 40.695% on the final leaderboard, namely Xiong team 1 .
Hepatolithiasis: A Dangerous Spectral End Point of Stone Disease

Hepatolithiasis is one of the most complex stone disease of the hepatobiliary system. The disease causes significant damage to the liver including the chance of developing a cholangiocarcinoma. Though the disease is rampant in East Asian countries isolated cases are seen even on the Indian subcontinent. Since experience is lacking in our country to treat this uncommon condition awareness of this condition will enable the surgeon diagnose and develop a proper surgical treatment plan which best suits the patient depending upon the severity of the disease process. A brief review of the etiopathogenesis, diagnosis and management is presented in this paper. Keywords— Hepatic Lithiasis Diagnosis Management.
Study of relationship between anemia and urinary tract infection in pregnant women

Background: Pregnancy is a state of decreased immunity . Physiological changes occurring in the pregnancy make women susceptible to urinary tract infection (UTI), more so in anemic pregnant women. The global prevalence of bacteriuria in pregnancy ranges from 4% to 23% in various studies. Maternal anemia has been associated with both asymptomatic bacteriuria and pyelonephritis. Materials and Method: This cross sectional study was conducted to determine the relationship of UTI with anemia in pregnant women attending antenatal clinic in tertiary centre, KIMS Hubli. A total of 100 pregnant women were enrolled in this study. The sample was divided into two study groups cases and controls. The cases group had Hb level of <10 gm% and control group had Hb level >/= 10gm%. Hemoglobin estimation was done by sahli's method. Anemia was classified accordingly. UTI was diagnosed using mid stream urine (MSU) culture, using >10 5 colony forming unit per millilitre as significant level of bacteriuria. Result: The overall prevalence was found to be 26%. There was a high prevalence of UTI of about 40% in anemic pregnant women (whose Hb was <10 gm %) as compared to 12% in non anemic pregnant women (whose Hb was 10 gm %). The mean blood Hb was significantly lower in UTI case (8.2%). There was high prevalence in 21-25yrs age group and also in 2nd trimester (75%). Multiparity is associated with increased UTI in pregnancy. E.coli was most frequently isolated pathogen (61%). Conclusion: We can conclude that there is an association between UTI and anemia of different causes during pregnancy. There was a high risk of having anemia amongst the complicated pregnancy with UTI in association with their parity, age and gestational age.
Using RDFa to Link Text and Dictionary Data for Medieval French

This paper presents an endeavor to transform a scholarly text edition (of a medical treatise written in Middle French) into a digital edition enriched with references to an on-line dictionary. Hitherto published as a book, the resulting digital edition will use RDFa to interlink its vocabulary with the corresponding lexical entries of the Dictionnaire étymologique de l’ancien français (DEAF). We demonstrate the feasibility of RDFa for the semantic enrichment of digital editions within the philologies. In particular, the technological support for RDFa excels beyond domain-specific solutions favored by the TEI community. Our findings may thus contribute to future technological bridges between TEI/XML and (Linguistic) Linked Open Data resources. The original data of the edition is available in a LTEX format that includes profound semantic markup. We convert this data into XML/TEI, and integrate RDFa-compliant attributes for every lexeme attested in the text. The HTML5 edition generated from the XML sources preserves the RDFa attributes and thus (a) embeds (links) its vocabulary within the overall system of the medieval French language, and that (b) provides and displays linguistic features (say, sense definitions given in the original corpus data) along with the critical apparatus of the original book publication.
Neural time series models with GluonTS Time Series Workshop ICML 2019

We introduce GluonTS, the Gluon Time Series Toolkit, a library for deep learning based time series modeling. GluonTS simplifies the development of and experimentation with time series models for common tasks such as forecasting or anomaly detection. It provides all necessary components and tools that scientists need for quickly building new models, for efficiently running and analyzing experiments and for evaluating model accuracy.