Miracle-dz/UniFAR-FTUs huggingface dataset:
Pricing Behavior of Multiproduct Retailers

This paper develops a model of competition among multiproduct retailers that is consistent with observed pricing regularities, such as the facts that virtually all products have large mass points in their price distributions and that most deviations fall below these mass points. The basis of the model is that, when consumers prefer to buy a bundle of goods from the same retailer, a given discount on any one good in the bundle will have a similar effect on consumers' likelihood of visiting that retailer. Consequently, discounts on goods sold by a retailer are substitute instruments for attracting customers, and factors that influence one goods' price will also affect other goods' prices. Hence, if intertemporal price changes are a means of price discriminating (as the literature suggests), then the impact of these changes will be reflected in the prices of many goods - including those for which discrimination is infeasible.
Boosting Unsupervised Relation Extraction by Using NER

Web extraction systems attempt to use the immense amount of unlabeled text in the Web in order to create large lists of entities and relations. Unlike traditional IE methods, the Web extraction systems do not label every mention of the target entity or relation, instead focusing on extracting as many different instances as possible while keeping the precision of the resulting list reasonably high. URES is a Web relation extraction system that learns powerful extraction patterns from unlabeled text, using short descriptions of the target relations and their attributes. The performance of URES is further enhanced by classifying its output instances using the properties of the extracted patterns. The features we use for classification and the trained classification model are independent from the target relation, which we demonstrate in a series of experiments. In this paper we show how the introduction of a simple rule based NER can boost the performance of URES on a variety of relations. We also compare the performance of URES to the performance of the state-of-the-art KnowItAll system, and to the performance of its pattern learning component, which uses a simpler and less powerful pattern language than URES.
Research on the Security of Microsoft’s Two-Layer Captcha

Captcha is a security mechanism designed to differentiate between computers and humans, and is used to defend against malicious bot programs. Text-based Captchas are the most widely deployed differentiation mechanism, and almost all text-based Captchas are single layered. Numerous successful attacks on the single-layer text-based Captchas deployed by Google, Yahoo! , and Amazon have been reported. In 2015, Microsoft deployed a new two-layer Captcha scheme. This appears to be the first application of two-layer Captchas. It is, therefore, natural to ask a fundamental question: is the two-layer Captcha as secure as its designers expected? Intrigued by this question, we have for the first time systematically analyzed the security of the two-layer Captcha in this paper. We propose a simple but an effective method to attack the two-layer Captcha deployed by Microsoft, and achieve a success rate of 44.6% with an average speed of 9.05 s on a standard desktop computer (with a 3.3-GHz Intel Core i3 CPU and 2-GB RAM), thus demonstrating clear security issues. We also discuss the originality and applicability of our attack, and offer guidelines for designing Captchas with better security and usability.
Neuro-fuzzy off-line recognition of handwritten sentences

Presents Beatrix, a system for off-line recognition of handwritten sentences. The system consists of four subsystems: the first pre-processes the input bitmap and splits each sentence into words; the second integrates neural and fuzzy logic techniques for individual character recognition; the third carries out a lexical and grammatical analysis of the recognised text; and the fourth uses the words recognised with a high confidence value to re-train the second subsystem on the specific handwriting. The analysis performed by the third subsystem produces hypotheses about words and sentences in order to correct errors made by the second subsystem. The fourth subsystem allows the system to self-adapt to the specific handwriting under examination; therefore, the system possesses the properties of both writer-independent and writer-dependent systems.
Multiuser detection in multipath environments for variable spreading-factor CDMA systems

A way to allow variable data rates in CDMA is by varying the spreading factor in accordance with the data rate requested by the user. A detection scheme suitable for multirate transmission is required in addition to one that combats multiple access interference of other users and intersymbol interference from multipath. In this letter, an energy-add multiuser detection method is combined with a scheme called Cholesky-iterative detection to cope with these challenges. It allows the users to be estimated on a symbol-by-symbol basis, making receiver complexity independent of data package length. Simulation results correspond closely to a single-user lower bound. The results also show that the bit-error probability performances of the various users for the Cholesky-iterative detector are closely clustered, while those of a previously published scheme, decorrelation feedback detection, are more widely spread.
A PARSIMONIOUS CONTINUOUS TIME MODEL OF EQUITY INDEX RETURNS: INFERRED FROM HIGH FREQUENCY DATA

In this paper we propose a continuous time model capable of describing the dynamics of futures equity index returns at different time frequencies. Unlike several related works in the literature, we avoid specifying a modela prioriand we attempt, instead, to infer it from the analysis of a data set of 5-minute returns on the S&P500 futures contract. We start with a very general specification. First we model the seasonal pattern in intraday volatility. Once we correct for this component, we aggregate intraday data into a daily volatility measure to reduce the amount of noise and its distorting impact on the results. We then employ this measure to infer the structure of the stochastic volatility model and of the leverage component, as well as to obtain insights on the shape of the distribution of conditional returns. Our model is then refined at a high frequency level by means of a simple nonlinear filtering technique, which provides an intraday update of volatility and return density estimates on the basis of observed 5-minute returns. The results from a Monte Carlo experiment indicate that a sample of returns simulated according to our model successfully replicates the main features observed in market returns.
Towards a Universal Content-Based Image and Video Retrieval System

Content-based retrieval allows to find information by searching about its content rather than about attributes like keywords. Based on the current state of content-based image and video retrieval, this paper addresses this problem in distributed environments with large, heterogeneous, and dynamically changing data repositories. Besides motivation, it describes an appropriate system architecture, and outlines an automatic and generic retrieval approach based on invariants.
Disrupted Bone Remodeling Leads to Cochlear Overgrowth and Hearing Loss in a Mouse Model of Fibrous Dysplasia

Normal hearing requires exquisite cooperation between bony and sensorineural structures within the cochlea. For example, the inner ear secretes proteins such as osteoprotegrin (OPG) that can prevent cochlear bone remodeling. Accordingly, diseases that affect bone regulation can also result in hearing loss. Patients with fibrous dysplasia develop trabecular bone overgrowth resulting in hearing loss if the lesions affect the temporal bones. Unfortunately, the mechanisms responsible for this hearing loss, which could be sensorineural and/or conductive, remain unclear. In this study, we used a unique transgenic mouse model of increased Gs G-protein coupled receptor (GPCR) signaling induced by expression of an engineered receptor, Rs1, in osteoblastic cells. These ColI(2.3)+/Rs1+ mice showed dramatic bone lesions that histologically and radiologically resembled fibrous dysplasia. We found that ColI(2.3)+/Rs1+ mice showed progressive and severe conductive hearing loss. Ossicular chain impingement increased with the size and number of dysplastic lesions. While sensorineural structures were unaffected, ColI(2.3)+/Rs1+ cochleae had abnormally high osteoclast activity, together with elevated tartrate resistant acid phosphatase (TRAP) activity and receptor activator of nuclear factor kappa-B ligand (Rankl) mRNA expression. ColI(2.3)+/Rs1+ cochleae also showed decreased expression of Sclerostin (Sost), an antagonist of the Wnt signaling pathway that normally increases bone formation. The osteocyte canalicular networks of ColI(2.3)+/Rs1+ cochleae were disrupted and showed abnormal osteocyte morphology. The osteocytes in the ColI(2.3)+/Rs1+ cochleae showed increased expression of matrix metalloproteinase 13 (MMP-13) and TRAP, both of which can support osteocyte-mediated peri-lacunar remodeling. Thus, while the ossicular chain impingement is sufficient to account for the progressive hearing loss in fibrous dysplasia, the deregulation of bone remodeling extends to the cochlea as well. Our findings suggest that factors regulating bone remodeling, including peri-lacunar remodeling by osteocytes, may be useful targets for treating the bony overgrowths and hearing changes of fibrous dysplasia and other bony pathologies.
Agile Software Development Practices in Distributed Environments

Agile is rapidly becoming one of the most popular software development methodologies across the globe. Companies throughout the world are making considerable efforts to shift from the traditional software development methods towards the agile practices. Distributed software development is an increasingly vital development approach for software companies throughout the world, as it brings additional opportunities. Moreover, the limitations of the localized projects can be overcome in the distributed projects. Distributed development is already burdened with several challenges and agile methodology brings further challenges. Till now, there has been a little empirical research on distributed agile software development. The paper reviews various sources and case studies for distributed agile software development, and discusses the challenges faced by such development teams. Possible recommendations for these challenges are presented as well.
Atom made from charged elementary black hole

It is believed that there may have been a large number of black holes formed in the very early universe. These would have quantised masses. A charged ``elementary black hole'' (with the minimum possible mass) can capture electrons, protons and other charged particles to form a ``black hole atom''. We find the spectrum of such an object with a view to laboratory and astronomical observation of them, and estimate the lifetime of the bound states. There is no limit to the charge of the black hole, which gives us the possibility of observing Z>137 bound states and transitions at the lower continuum. Negatively charged black holes can capture protons. For Z>1, the orbiting protons will coalesce to form a nucleus (after beta-decay of some protons to neutrons), with a stability curve different to that of free nuclei. In this system there is also the distinct possibility of single quark capture. This leads to the formation of a coloured black hole that plays the role of an extremely heavy quark interacting strongly with the other two quarks. Finally we consider atoms formed with much larger black holes.
Decentralized formation control of autonomous mobile robots

Control of vehicle formations is an area of great interest that requires knowhow from several scientific areas such as control theory, vision, communication system, etc. In this work, several approaches to maintain a formation of vehicles are explained and tested. In this paper, the approach towards formation control is achieved through Position Based Visual Servoing (PBVS). In PBVS, a cartesian space controller is used for target tracking. Two 2D pose estimation methods are described and two local controllers developed (Discrete Linear Quadratic Regulator and an explicit Model Predictive Controller). To maintain the mobile robots in formation, a Neighbor Referenced (NR) control scheme is used. NR-based control allows decentralized formation control schemes since each member of the formation only has information of its neighbors and not of the entire robots in the formation. Finally, simulation and experimental results of the developed work are presented.
Pattern computation for compression garment

This paper addresses the problem of computing planar patterns for compression garments. In the garment industry, the compression garment has been more and more widely used to retain a shape of human body, where certain strain (or normal pressure) is designed at some places on the compression garment. Variant values and distribution of strain can only be generated by sewing different 2D patterns and warping them onto the body. We present a physical/geometric approach to compute 2D meshes that, when folded onto the 3D body, can generate a user-defined strain distribution through proper distortion. This is opposite to the widely studied mesh parameterization problem, whose objective is to minimize the distortion between the 2D and 3D meshes in angle, area or length.
The Fraunhofer IESE Experience Management System

Experience Management (EM) is an area that is increasingly gaining importance. Its roots lie in Experimental Software Engineering ("Experience Factory"), in Artificial Intelligence ("Case-Based Reasoning"), and in Knowledge Management. EM is comprised of the dimensions methodology, technical realization, organization, and management. It includes techniques, methods, and tools for identifying, collecting, documenting, packaging, storing, generalizing, reusing, adapting, and evaluating experience, as well as for development, improvement, and execution of all knowledge-related processes. The main difference between experience and more general knowledge is the fact that normally, a (more or less) continuous "stream of knowledge" must be processed. Within this contribution, we present the Fraunhofer IESE Experience Factory as a practical example for an experience management system, which is in operation for more than two years.
Compact modeling for gate-all-around nanowire tunneling FETs (GAA NW-tFETs)

A compact model for gate-all-around (GAA) nanowire tunneling FETs (NW-tFETs) is developed based on ballistic transport and charge balancing approaches. To account for the carrier injection to the channel from source/drain (S/D) regions for NW FETs, the density-of-states (DOS) charge, which results in the so-called quantum capacitance, is introduced and augmented to include tunneling phenomenon. A complete large-signal equivalent circuit is proposed for the first time, including the doping effects in S/D regions. Preliminary results from comparison of model prediction and numerical device simulation show the correctness of the modeling methodology.
Cryptorchestia ruffoi sp. n. from the island of Rhodes (Greece), revealed by morphological and phylogenetic analysis (Crustacea, Amphipoda, Talitridae)

Abstract A new Cryptorchestia species, Cryptorchestia ruffoi Latella & Vonk, sp. n. from the island of Rhodes in south-eastern Greece, can be distinguished on the basis of morphological and phylogenetic data. Morphological analysis and DNA sequencing of mitochondrial and nuclear protein-coding genes indicated that this species is related to Cryptorchestia cavimana (Cyprus) and Cryptorchestia garbinii (Mediterranean regions, with a recent northward expansion). Results supported a genetic separation between the Cryptorchestia species of the east Mediterranean regions and those of the northeast Atlantic volcanic islands examined in this study (Cryptorchestia canariensis, Cryptorchestia gomeri, Cryptorchestia guancha, and Cryptorchestia stocki from the Canary islands, Cryptorchestia monticola from Madeira, and Cryptorchestia chevreuxi from the Azores). The Mediterranean and Atlantic Cryptorchestia species appear to be also morphologically distinct. Cryptorchestia ruffoi sp. n. , Cryptorchestia cavimana, Cryptorchestia garbinii, and Cryptorchestia kosswigi (Turkish coast) clearly have a small lobe on the male gnathopod 1 merus. This character was the main diagnostic difference between Cryptorchestia (sensu Lowry, 2013) and Orchestia. However, among the six northeast Atlantic island Cryptorchestia species only Cryptorchestia stocki has a small lobe on the merus of gnathopod 1. Reduction or loss of the lobe in the Atlantic Island species cannot be ruled out; however, molecular phylogenetic analysis leads us to presume that this lobe independently evolved between the east Mediterranean Cryptorchestia species and Cryptorchestia stocki from Gran Canaria.
Multiband optical observations of the old PSR B0950+08

We report on deep UBVRI -imaging of the field of the 17.3 Myr radiopulsar PSR B0950+08 obtained with the ESO/VLT/FORS1. Firm detection of the candidate pulsar optical counterpart in the BVRI bands with the magnitudes $B=27.06$ ± 0.35, $V=27.05$ ± 0.15, $R_{\rm c}=26.49$ ± 0.10 and $I_{\rm c}=26.20$ ± 0.17 enabled us to study, for the first time, the broadband spectrum of the object. The derived ~$0\farcs24$ offset of the object from the radiopulsar position is insignificant within the $ 0\farcs21$ uncertainties of our astrometry and ~$0\farcs75$ seeing value during the observations. The positional coincidence and unusual colors of the candidate ensure us that we likely detect the optical emission from PSR B0950+08. The optical-near-UV spectrum of the pulsar has a negative slope and can be fitted by a power law ${F_\nu \propto \nu^{-\alpha}}$ with ${\rm \alpha=0.65}$ ± 0.40, suggesting nonthermal emission. Within errors the optical flux is consistent with the power law fit of the ROSAT spectrum from the X-ray counterpart. We analyze our results together with the available multiwavelength data on other isolated pulsars of different ages detected in the optical range and find a significant correlation between their optical and 2–10 keV X-ray luminosities. This implies an origin of the nonthermal emission in both spectral domains. These objects show a significantly non-monotonic evolution of the efficiency of the optical-X-ray photon production from the pulsar spindown power, with a pronounced minimum at the beginning of the middle-age epoch and comparably high efficiencies of younger and older pulsars. This suggests different sensitivities of the photon production processes to the Goldreich-Julian current in magnetospheres of different age pulsars.
Estimating the Parameters of a Small Open Economy DSGE Model: Identifiability and Inferential Validity

This paper estimates the parameters of a stylized dynamic stochastic general equilibrium model using maximum likelihood and Bayesian methods, paying special attention to the issue of weak parameter identification. Given the model and the available data, the posterior estimates of the weakly identified parameters are very sensitive to the choice of priors. We provide a set of tools to diagnose weak identification, which include surface plots of the log-likelihood as a function of two parameters, heat plots of the log-likelihood as a function of three parameters, Monte Carlo simulations using artificial data, and Bayesian estimation using three sets of priors. We find that the policy coefficients and the parameter governing the elasticity of labor supply are weakly identified by the data, and posterior predictive distributions remind us that DSGE models may make poor forecasts even when they fit the data well. Although parameter identification is model- and data-specific, the lack of identification of some key structural parameters in a small-scale DSGE model such as the one we examine should raise a red flag to researchers trying to estimate - and draw valid inferences from - large-scale models featuring many more parameters.
Investigating the syntactic structure of Arabic sentences

In this paper, we employ the Government and Binding theory (GB) to present a system that analyzes the syntactic structure of some simple Arabic sentences structures. We consider different word orders in Arabic and show how they are derived. We include an analysis of Subject-Verb-Object (SVO), Verb-Object-Subject (VOS), Verb-Subject-Object (VSO), nominal sentences, nominal sentences with inna (or sisters), and question sentences. We use the analysis to develop syntactic rules for a fragment of Arabic, such that we include two sets of rules (1) rules on sentences structures that do not account for case and (2) rules on sentences structures that account for Noun Phrases (NPs) case. We present an implementation of the grammar rules in prolog. The results of testing the system t were reasonable with a high accuracy especially when the input sentences are tagged with identification of end cases.
50 years of fusion research

Fusion energy research began in the early 1950s as scientists worked to harness the awesome power of the atom for peaceful purposes. There was early optimism for a quick solution for fusion energy as there had been for fission. However, this was soon tempered by reality as the difficulty of producing and confining fusion fuel at temperatures of 100 million °C in the laboratory was appreciated. Fusion research has followed two main paths—inertial confinement fusion and magnetic confinement fusion. Over the past 50 years, there has been remarkable progress with both approaches, and now each has a solid technical foundation that has led to the construction of major facilities that are aimed at demonstrating fusion energy producing plasmas.
An ordered weighted operator approach towards web usage mining

Regression analysis is one of the techniques of data mining and is used to generate futuristic model for a given problem. One of the major challenge in the study of Regression analysis is to reduce the Outlier values. But the inherent complex and flexible nature of web data makes it difficult for various regression algorithms to propose an ideal futuristic model. This paper discusses a method that tries to reduce Outlier values by using a variant of Ordered Weighted Operators. First, a regression problem will be formulated and then it will be converted into a Multi-criteria decision making problem. Results, thus obtained will show that the outliers can be reduced to a significant extent by proper use of these operators.
Laser Microtools in Cell Biology and Molecular Medicine

Lasers for micromanipulation in cellular or subcellular dimensions have gained remarkable interest within the entire community of life science research and applications. In 1962, Bessis, for the first time, focused a ruby laser into a microscope to perform micromanipulation of cells under microscopic observation (1). Today, there exist two principles of laser micromanipulation that depend on the nature of the applied laser source. So- called "optical traps" are generated by coupling a continuous wave near an infrared laser into a routine micro- scope. Optical forces are generated within the small laser focal spot that attract microscopic small specimens and hold them there solely by radiation pressure forces. On the other hand, a focused, near diffraction limited pulsed UVA laser allows ablation and microdissection of biological material with high spatial resolution. There, focal diameters of less than 500 nm can be achieved depending on the numerical aperture of the applied objec- tive. These laser-based systems are the state of the art technologies for precise and noncontact micromanipula- tions with nanometer accuracy and have become indispensable tools in modern medicine and biotechnology, as will be outlined in this review article.