Miracle-dz/UniFAR-FTUs huggingface dataset:
Small and Medium-sized Enterprises' Credit Rationing on the Tunisian Bank Credit Market

We use a disequilibrium model to estimate credit rationing to Small and Medium-sized Enterprises (SMEs) on the Tunisian bank credit market. Based on a panel dataset of 1,275 SMEs over the period 2001-2006, results show that the demand for bank credit is not determined by " endogenous " factors, i.e. the activity level and internal available resources of SMEs, but rather by " exogenous " factors, i.e. the cost of financing and guarantees required by banks. The latter, especially real guarantees, explain to a large extent the lack of bank lending and results in an average share of 80% — partially or totally — credit rationed SMEs.
At-sea distribution and behaviour of a surface-feeding seabird, the lesser black-backed gull Larus fuscus, and its association with different prey

The lesser black-backed gull Larus fuscus is a typical surface-feeding seabird with a widespread, patchy distribution in the SE North Sea. During the 1990s, breeding numbers along the German North Sea coast increased exponentially. Analyses of a multiple-year data set revealed changes in the at-sea distribution that seemed to reflect an increase in the numbers of breeding birds. Detailed recordings of feeding and resting behaviour at sea revealed area utilisation by the lesser black-backed gull. Observations at sea and dietary analysis revealed that swimming crabs Liocarci- nus spp. are a major dietary item of this gull species. This natural food source was primarily captured close to the shore; at longer distances from the coast the gulls mainly fed on other natural prey items or discarded fishes from trawlers and avoided competition with other breeding gull species. During July and August 1990 to 1995 L. fuscus abundance was significantly correlated with fishing effort, while in May and June there was no such correlation. Time of day was the main environmental vari- able influencing the gulls' flight activity and indicated an association between activity and availabil- ity of their major natural prey, swimming crabs. Distinct patterns and changes in the at-sea distribu- tion and foraging behaviour of L. fuscus in the SE North Sea reflect anthropogenic and natural influences in their habitats.
Supervisory Control of Systems Modeled by Petri Net from Adequate Admissible Constraints

: The purpose of Supervisory Control of the system, considered as Discrete Event Systems (SED), is to synthesize an optimal and non-blocking controller. Indeed, the specifications of the SED are generally declined in forbidden states that must be avoided. Our work consisted in finding a structural synthesis approach based on the determination of the adequate admissible constraints stresses for the Petri net (PN) invariant method. The closed-loop system model (SED) is obtained by synchronous product of elementary PNs. First, we used the computational power of the Kumar algorithm based on finite state automata to determine the constraints related to forbidden states. But, exploration of the PN marking graph is laborious. This is what led us second, to represent the reachable marking graph by its transition matrix. The coding of this matrix, according to the state specification, allowed us to separate the states and identify the states relevant to the synthesis of a controller.
MSISpIC: A Probabilistic Scan Matching Algorithm Using a Mechanical Scanned Imaging Sonar

This paper compares two well known scan matching algorithms: the MbICP and the pIC. As a result of the study, it is proposed the MSISpIC, a probabilistic scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), and the robot displacement estimated through dead-reckoning with the help of a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. Its major contribution consists in: 1) using an EKF to estimate the local path traveled by the robot while grabbing the scan as well as its uncertainty and 2) proposing a method to group into a unique scan, with a convenient uncertainty model, all the data grabbed along the path described by the robot. The algorithm has been tested on an AUV guided along a 600m path within a marina environment with satisfactory results.
Comparing Index Structures for Completeness Reasoning

Data quality is a major issue in the devel- opment of knowledge graphs. Data completeness is a key factor in data quality pertaining to how broad and deep is information contained in knowledge graphs. As for large- scale knowledge graphs (e.g., DBpedia, Wikidata), it is conceivable that given the vast amount of information contained in there, they may be complete for a wide range of topics, such as children of Joko Widodo, cantons of Switzerland, and presidents of Indonesia. Previous research has shown how one can augment knowledge graphs with statements about their completeness, stating which parts of data are complete. Such meta-information can be leveraged to check query completeness, that is, whether the answer returned by a query is complete. Yet, it is still unclear how such a check can be done in practice, especially when many completeness statements are involved. We devise implementation techniques to make completeness reasoning in the presence of large sets of completeness statements feasible, and experimentally evaluate their effectiveness in realistic settings based on the characteristics of real-world knowledge graphs.
Recurrent Bilateral Breast Abscess in Immunocompetent Women: A Case Report and Literature Review

Breast abscess is a localized pocket of infection containing pus tissue; that commonly affects women of reproductive years with age ranging from 18-50 years. It is divided into a lactation and non-lactation infection. It can affect overlying skin as a primary event or secondary to a lesion such as sebaceous cyst [1]. Breast abscesses are typically caused by bacteria, most commonly Staphylococcus aureus. Other causes include mycobacterial and fungal infections [2]. There have been few reports of different infections caused by Salmonella spp. in recent years and a single case of bilateral breast abscess caused by E. coli and few by Proteus mirabilis, to our knowledge, there were no cases reported with recurrent breast abscesses caused by Kocuria kristinae. We present an unusual case of recurrent bilateral breast abscess caused by multiple organisms in an immunocompetent non-lactating patient.
Tooling Framework for Instantiating Natural Language Querying System

Recent times have seen a growing demand for natural language querying (NLQ) interfaces to retrieve information from the structured data sources such as knowledge bases. Using this interface, business users can directly interact with a database without the knowledge of the query language or the data schema. Our earlier work describes a natural language query engine called ATHENA which has several shortcoming around ease of use and compatibility with data stores, formats and flows. In this demonstration paper, we present a tooling framework to address these challenges so that one can instantiate an NLQ system with utmost ease. Our framework makes it easy and practically applicable to all NLIDB scenarios involving different sources of structured data, file formats, and ontologies to enable natural language querying on top of them with minimal human configuration. We present the tool design and the solution to the challenges towards building such a system and demonstrate its applicability in the medical domain.
An XML fragment retrieval method with image and text using textual information retrieval techniques ( Extended Abstract )

In this paper, we propose a retrieval method using textual information retrieval techniques, such as vector space model, for XML documents which consist of image and text. Recently, many image retrieval systems are proposed. However, these systems are mainly based on pattern recognition techniques. Therefore, the features of images are also based on these recognition techniqus, such as color histogram, and shape of the object in images. Generally, these systems do not consider weight of features, which means how important these features are, which are generally used in textual information retrieval systems. In this paper, we propose a method considering weight, such as TFIDF, to identify the importance degree of features. Using our proposed method, the system can retrieve intuitively similar retrieval target images to user’s query images.
Local Derivative Post-processing : Challenges for a non-uniform mesh

Previous investigations into accuracy enhancement for the derivatives of a discontinuous Galerkin solution demonstrated that there are many ways to approach obtaining higher order accuracy in the derivatives, each with different advantageous properties. For the discontinuous Galerkin method, the order of accuracy without post-processing for the dth? derivative is k+1-d. For the derivative of the post-processed solution it is 2k+1-d. Additionally, it was demonstrated that not only is calculating the derivative of the post-processed solution itself unnecessary, but also that order 2k+1 can be obtained for the derivative solution for any order derivative, provided the solution is 2k+1 continuous. This is done using higher-order B-splines than used for the post-processed solution itself convolved against a finite difference derivative. This introduces higher levels of smoothness into the derivative post-processed approximation. However, this investigation was limited to a uniform mesh consideration, which is highly restrictive for practical applications. In this report, we discuss the advantages and disadvantages of extending accuracy enhancement of derivatives to non-uniform meshes in one-dimension using the ideas of local L2-projection, characteristic length as well as direct implementation as done for the post-processed solution itself.
X-ray interferometry and lattice parameter investigation

2014 The essentials of X-ray interferometry and its principal application fields are reviewed. Very small lattice disturbances which are present even in highest quality crystals of silicon have been investigated by ordinary and moire topography. Strains corresponding to 0394d/d variations of 10-7 are found in large perfect crystals. REVUE DE PHYSIQUE APPLIQUÉE TOME 11, JANVIER 1976, PAGE The principles of X-ray interferometry [1, 2, 3, 4, 5] are best and in a most illustrative way explained by means of the moire model [4] which, although simplifying, describes the essentials of interferometric defect study correctly. We consider the triple Laue case (LLL) interferometer of figure 1 with the diffracting net planes normal FIG. 1. LLL-interferometer, see text. to the wafer surfaces as indicated. X-rays of some wavelength A are Laue case diffracted, i. e. the reflected wave H propagates behind the crystal, by the three crystals named wave splitter S, mirror M and wave analyser A. Ideally S, M and A are all perfect crystals which have exact parallel orientation. The X-rays are coherently split by S, conducted over two widely separated beam paths I and II and superimposed in either outgoing beam 0 and H by diffraction from A. The outwardly reflected beams behind M are not used and can be eliminated by beam stops if necessary. We assume flt &#x3E; 1, where p is the normal absorption coefficient and t the thickness of the crystal wafers which for ease of discussion we assume to be equal for S, M and A. The boundary conditions for the electromagnetic field [6, 7, 8] when applied to the Laue case diffraction require the excitation of either kind of the two wavefield modes possible in the crystal : type 1 wavefield with its nodal planes between the planes of lattice atoms and type 2 wavefield with its nodes on the atoms. (If both Qand 03C0-polarization are considered then there are two modes for each state. For reasons of simplicity we neglect the 03C0-state.) The type 1 field experiences anomalous absorption and the type 2 field anomalous transmission [9]. With pt &#x3E; 1 the type 1 field is totally absorbed in the lattice and only the type 2 field emerges from the exit surface of the crystal. Here the boundary conditons require the continuity of the electric induction D inside and outside the crystal so that the nodal planes of the standing wave pattern which is set up by the transmitted 0 and H wave behind S (Ps in Fig. 1) point necessarily on the atomic planes of S. By means of M the image pattern PA of Ps in front of A is formed. If the atomic planes of S, M and A are all perfectly « in line » then, for reasons of symmetry, the nodal planes of PA will also point on the atomic planes of A. Continuity of D requires that in A solely the type 2 field is excited. It traverses A with little attenuation and emits one of its plane wave components into beam 0 and the other into beam H. Thus both beams have equal intensity which in addition is constant over the cross sections of 0 and H. Article published online by EDP Sciences and available at http://dx.doi. org/10.1051/rphysap:0197600110108300
Maestro: Designing a System for Real-Time Orchestration of 3D Modeling Workshops

Instructors of 3D design workshops for children face many challenges, including maintaining awareness of students' progress, helping students who need additional attention, and creating a fun experience while still achieving learning goals. To help address these challenges, we developed Maestro, a workshop orchestration system that visualizes students' progress, automatically detects and draws attention to common challenges faced by students, and provides mechanisms to address common student challenges as they occur. We present the design of Maestro, and the results of a case-study evaluation with an experienced facilitator and 13 children. The facilitator appreciated Maestro's real-time indications of which students were successfully following her tutorial demonstration, and recognized the system's potential to "extend her reach" while helping struggling students. Participant interaction data from the study provided support for our follow-along detection algorithm, and the capability to remind students to use 3D navigation.
The RAW Filter: An Improvement to the Robert–Asselin Filter in Semi-Implicit Integrations

AbstractErrors caused by discrete time stepping may be an important component of total model error in contemporary atmospheric and oceanic simulations. To reduce time-stepping errors in leapfrog integrations, the Robert–Asselin–Williams (RAW) filter was proposed by the author as a simple improvement to the widely used Robert–Asselin (RA) filter. The present paper examines the behavior of the RAW filter in semi-implicit integrations. First, in a linear theoretical analysis, the stability and accuracy are interrogated by deriving analytic expressions for the amplitude errors and phase errors. Then, power-series expansions are used to interpret the leading-order errors for small time steps and hence to identify optimal values of the filter parameters. Finally, the RAW filter is tested in a realistic nonlinear setting, by applying it to semi-implicit integrations of the elastic pendulum equations. The results suggest that replacing the RA filter with the RAW filter could reduce time-stepping errors in semi-im.
A Result Reconstruction Method for Effective XML Fragment Search at INEX 2010

In this paper, we propose an extension scheme of the re- sult reconstruction method that we previously proposed. In the previous method, we aimed to extract more relevant fragments without irrelevant parts. Since the challenge of Ad hoc track in INEX 2010 is to gener- ate "snippets" which return only small size of contents, we extend our method along the concept of INEX 2010. To generate meaningful snip- pets, we propose a novel way of extracting search results and adjust our previous methods to be suitable one for restricted results in its text size.
Analyses of the Watershed Transform

In the framework of mathematical morphology, watershed transform (WT) represents a key step in image segmentation procedure. In this paper, we present a thorough analysis of some existing watershed approaches in the discrete case: WT based on flooding, WT based on path-cost minimization, watershed based on topology preservation, WT based on local condition and WT based on minimum spanning forest. For each approach, we present detailed description of processing procedure followed by mathematical foundations and algorithm of reference. Recent publications based on some approaches are also presented and discussed. Our study concludes with a classification of different watershed transform algorithms according to solution uniqueness, topology preservation, prerequisites minima computing and linearity.
IIT (BHU) Varanasi at MSR-SRST 2018: A Language Model Based Approach for Natural Language Generation

This paper describes our submission system for the Shallow Track of Surface Realization Shared Task 2018 (SRST’18). The task was to convert genuine UD structures, from which word order information had been removed and the tokens had been lemmatized, into their correct sentential form. We divide the problem statement into two parts, word reinflection and correct word order prediction. For the first sub-problem, we use a Long Short Term Memory based Encoder-Decoder approach. For the second sub-problem, we present a Language Model (LM) based approach. We apply two different sub-approaches in the LM Based approach and the combined result of these two approaches is considered as the final output of the system.
EFFECTIVE AND EFFICIENT RULE MINING TECHNIQUE FOR INCREMENTAL DATASET

This paper presents an effective and efficient rule mining technique for incremental dataset. One of the most important challenge is discovering the frequent patterns , if the dataset is incremental in nature , this may cause some existing rules becomes invalid and some new rules becomes valid. In this paper, the Efficient Incremental Rule Mining (EIRM) Algorithm is proposed as a solution to this problem. In the proposed algorithm only a single scan to the database is needed. Instead of itemsets, the Transaction Identifiers (TIDs) are stored for discovering promising and unpromising item sets and relevant support count are also maintained. This helps to find all frequent patterns of an updated dataset efficiently and reduces execution time. The simulation results show that the proposed algorithm has good performance.
MULTIPLE CRITERIA DECISION ANALYSIS FOR HEALTH TECHNOLOGY ASSESSMENT REPORT

Acknowledgements The author is grateful for financial support from the NICE Decision Support Unit (DSU). NICE had no responsibility or control over the content of this paper. This paper aims to look at the applicability of multi criteria decision analysis (MCDA) for health technology assessment. MCDA is aimed at supporting decision makers faced with evaluating alternatives, taking into account multiple, and often conflictive, criteria. This manuscript begins with a critical review of state-of-the-art methods for incorporating multiple criteria in health technology assessment (HTA). An overview of MCDA is provided and is compared against the current NICE (National Institute for Health and Clinical Excellence) health technology appraisal process. A generic MCDA modelling approach is described and the most common types of MCDA models are detailed. The different MCDA modelling approaches are applied to a hypothetical case study. Finally, the issues that need to be considered for the application of MCDA in HTA are examined along with recommendations for future research. Most of the proposed MCDA approaches in literature use the same technique (weighted sum approach) which may lead to the researchers/health professionals assuming that it is the only relevant MCDA method. MCDA does not just stop at simple weighting and scoring; more flexible approaches are available that appear to be more relevant to the NICE appraisal process and value based pricing (VBP). There is a semblance between main MCDA modelling approaches and other techniques (such as programme budgeting and marginal analysis [PBMA], VBP and NICE recommended table of the summary characteristics). However, there are general practical issues that might arise from using an MCDA approach in the HTA process and it is suggested that appropriate care needs to be taken to address the issues identified in order to ensure the success of MCDA techniques in the appraisal process.
Recognizing Emotions in Video Using Multimodal DNN Feature Fusion

We present our system description of input-level multimodal fusion of audio, video, and text for recognition of emotions and their intensities for the 2018 First Grand Challenge on Computational Modeling of Human Multimodal Language. Our proposed approach is based on input-level feature fusion with sequence learning from Bidirectional Long-Short Term Memory (BLSTM) deep neural networks (DNNs). We show that our fusion approach outperforms unimodal predictors. Our system performs 6-way simultaneous classification and regression, allowing for overlapping emotion labels in a video segment. This leads to an overall binary accuracy of 90%, overall 4-class accuracy of 89.2% and an overall mean-absolute-error (MAE) of 0.12. Our work shows that an early fusion technique can effectively predict the presence of multi-label emotions as well as their coarse-grained intensities. The presented multimodal approach creates a simple and robust baseline on this new Grand Challenge dataset. Furthermore, we provide a detailed analysis of emotion intensity distributions as output from our DNN, as well as a related discussion concerning the inherent difficulty of this task.
Highly Chemo‐ and Regioselective Transfer Reduction of Aromatic Nitro Compounds using Ammonium Formate Catalyzed by Supported Gold Nanoparticles

A highly chemo- and regioselective reduction of a wide diversity of aromatic nitro compounds to the corresponding amines has been achieved by a combination of gold nanoparticles supported on titania and ammonium formate (HCOONH 4 ) in ethanol at room temperature. Furthermore, a direct and mild route to formanilides from aromatic nitro compounds bearing different functional groups by reductive N-formylation using the gold-mediated transfer reduction protocol is also established.
Spatiotemporal Analysis of Coronal Loops Using Seismology of Damped Kink Oscillations and Forward Modeling of EUV Intensity Profiles

The shape of the damping profile of kink oscillations in coronal loops has recently allowed the transverse density profile of the loop to be estimated. This requires accurate measurement of the damping profile that can distinguish the Gaussian and exponential damping regimes, otherwise there are more unknowns than observables. Forward modeling of the transverse intensity profile may also be used to estimate the width of the inhomogeneous layer of a loop, providing an independent estimate of one of these unknowns. We analyze an oscillating loop for which the seismological determination of the transverse structure is inconclusive except when supplemented by additional spatial information from the transverse intensity profile. Our temporal analysis describes the motion of a coronal loop as a kink oscillation damped by resonant absorption, and our spatial analysis is based on forward modeling the transverse EUV intensity profile of the loop under the isothermal and optically thin approximations. We use Bayesian analysis and Markov chain Monte Carlo sampling to apply our spatial and temporal models both individually and simultaneously to our data and compare the results with numerical simulations. Combining the two methods allows both the inhomogeneous layer width and density contrast to be calculated, which is not possible for the same data when each method is applied individually. We demonstrate that the assumption of an exponential damping profile leads to a significantly larger error in the inferred density contrast ratio compared with a Gaussian damping profile.