Miracle-dz/UniFAR-FTUs huggingface dataset:
Leveraging Leveraging Knowledge Knowledge Reuse Reuse and and System System Agility Agility in in the the Outsourcing Outsourcing Era Era

Abstract Collaborative work groups that span multiple locations and time zones, or “follow the sun,” create a growing demand for creating new technologies and methodologies that enable traditional spatial and temporal separations to be surmounted in an effective and productive manner. The hurdles faced by members of such virtual teams are in three key areas: differences in concepts and terminologies used by the different teams, differences in understanding the problem domain under consideration, and differences in training, knowledge, and skills that exist across the teams. These reasons provide some of the basis for the delineation of new architectural approaches that can normalize knowledge and provide reusable artifacts in a knowledge repository.
Pathwise Stochastic Optimal Control

This paper approaches optimal control problems for discrete-time controlled Markov processes by representing the value of the problem in a dual Lagrangian form; the value is expressed as an infimum over a family of Lagrangian martingales of an expectation of a pathwise supremum of the objective adjusted by the Lagrangian martingale term. This representation opens up the possibility of numerical methods based on Monte Carlo simulation, which may be advantageous in high-dimensional problems or in problems with complicated constraints.
Protecting Websites with Reading-Based CAPTCHAs

Recent document image understanding R&D intended to protect Internet services against abuse by programs is summarized. The accelerating pace of introduction of working CAPTCHAs — completely automatic public Turing tests to tell computers and humans apart — is reported, and the ability of these CAPTCHAs to resist attack is critiqued. Attacks on PARC’s ‘BafﬂeText’ CAPTCHA by the DIA, CV, and security communities are cordially invited by a PARC website www.parc. com/istl/projects/captcha .
iOLAP: A Framework for Analyzing the Internet, Social Networks, and Other Networked Data

As the amount of noisy, unorganized, linked data on the Internet increases dramatically, how to efficiently analyze such data becomes a challenging research problem. In this paper, we propose a framework, iOLAP, that offers functionalities for analyzing networked data from Internet, social networks, scientific paper citations, etc. We first identify four main data dimensions that are common in most of networked data, namely people, relation, content, and time. Motivated by the fact that various dimensions of data jointly affect each other, we propose a polyadic factorization approach to directly model all the dimensions simultaneously in a unified framework. We provide detailed theoretical analysis of the new modeling framework. In addition to the theoretical framework, we also present an efficient implementation of the algorithm that takes advantage of the sparseness of data and has time complexity linear in the number of data records in a dataset. We then apply the proposed models to analyzing the blogosphere and personalizing recommendation in paper citations. Extensive experimental studies showed that our framework is able to provide deep insights jointed obtained from various dimensions of networked data.
Initialisation and Termination of Active Contour Level-Set Evolutions

This paper deals with the evolution control of level-sets in the context of contour detection. There is a considerable amount of existing work on PDEs for geodesic contour detection and the investigation of level-set implementation s has recently resulted in efficient and stable numerical realisa tions of the differential evolution. This paper is based on a finite element implementation for signed distance level-s et evolutions and focuses the attention to the initialisation and termination of level-set evolutions. An initialisation co nsists of an initial signed distance function which corresponds to some implicit curve. We discuss two types of initialisation . We generalise the commonly used a priori type, which can be a rectangle the size of the image, to include more general initial shapes. We show that the initial shape does not have to be closed and can for instance be a single line. The second type of initialisations is not specified by the user but a result of previous level-set evolutions. This type of initi alisation is useful when different evolution equations are to b e alternated and can be used for instance to detect nested contours or in multi-resolution techniques. For the terminati on of a geodesic evolution, we introduce an automatic stopping condition by looking at the Riemannian length of the implici t curve as the quantity that is subject to the minimisation. It turns out that the length can be computed efficiently from the employed finite element representation and used to terminat e the gradient descent.
Effects of an implantable two-channel peroneal nerve stimulator versus conventional walking device on spatiotemporal parameters and kinematics of hemiparetic gait.

OBJECTIVE The aims of this study were: (i) to compare the neuro-prosthetic effect of implantable peroneal nerve stimulation to the orthotic effect of a standard of care intervention (no device, shoe or ankle foot orthosis) on walking, as assessed by spatiotemporal parameters; and (ii) to examine whether there is evidence of an enhanced lower-limb flexion reflex with peroneal nerve stimulation and compare the kinematic effect of an implantable peroneal nerve stimulation device vs standard of care intervention on initial loading response of the paretic limb, as assessed by hip, knee and ankle kinematics. DESIGN Randomized controlled trial. SUBJECTS A total of 23 chronic stroke survivors with drop foot. METHODS The intervention group received an implantable 2-channel peroneal nerve stimulator for correction of drop foot. The control group continued using a conventional walking device. Spatiotemporal parameters and hip, knee and ankle kinematics were measured while subjects walked with the device on using a 3-dimensional video camera system during baseline and after a follow-up period of 26 weeks. RESULTS Peroneal nerve stimulation normalized stance and double support of the paretic limb and single support of the non-paretic limb, in comparison with using a conventional walking device. In addition, peroneal nerve stimulation is more effective to provide ankle dorsiflexion during swing and resulted in a normalized initial loading response. CONCLUSION Although peroneal nerve stimulation and ankle foot orthosis are both prescribed to correct a drop foot in the same patient population, spatiotemporal parameters, dorsiflexion during swing and loading response are influenced in a functionally different way.
Compressive sensing for improved MIMO radar performance — A review

Multiple-input multiple-output (MIMO) radar systems have received much attention in recent times due to their ability to detect and estimate targets better. These radar systems utilize multiple transmit waveforms, either orthogonal or non-orthogonal, providing additional diversity to improve on delay-Doppler as well as angular resolutions. Recent advances in Compressive Sensing (CS) offer an effective means to address for further performance improvements in MIMO radar signal processing. CS based MIMO radar systems emphasize the inherent target sparsity in the target space and aim to achieve better resolution while using considerably reduced number of measurements; or significantly enhance the radar performance for the same number of measurements. The benefits of data volume reduction appears as savings in memory and power, as well as lowering the acquisition time. In this paper, a number of representative and recent articles pertaining to CS techniques in MIMO radar systems are reviewed and categorized. The discussion here particularly emphasizes the various design techniques that improve the MIMO radar performance.
Financial reporting: profitability ratios in the different stages of life cycle

This study develops a mathematical framework to analyze the time-series of profitability ratios across different stages of life cycle. This study extends the analysis of ratios in the early stages of a startup outlined by Laitinen (2017) to contribute to the life cycle research. The growth of expenditure is assumed to consist of the difference of two steady growth processes: stand-alone growth and growth of competition impact. If the growth rate of competition impact exceeds the stand-alone growth rate, an S-shaped curve as a life cycle is resulted. Each periodic expenditure is assumed to generate a proportionally identical flow of revenue with a constant internal rate of return (IRR) and distributed geometric lag structure. The firm is expensing in each period a fixed part of periodic expenditure and beginning-of-the-period assets. It is shown that the time-series of profitability ratios are sensitive especially to the rate of expense emphasizing the role of expense method in financial reporting. If the rate of expense is not consistent with the revenue lag, profitability ratios show strong divergent variation (spread) across the early years (birth stage) and during the decline stage. Thus, in particular in these stages, profitability ratios are unable to reflect IRR properly.
The Evolution of Productivity-Wage Gaps Following the Transition in Hungary - Evidence from Linked Employer-Employee Data

We explore the relative productivities and wages of worker groups over a 20 year period following the transition in Hungary. Due to the economic transition, firms may have become more efficient in terms of setting wages, relative productivities and wages would converge over time. The linked employer-employee dataset allows us to control for selection bias at the occupation, firm, region, and industry level, and to assess long-term trends. The results do not suggest that firm wage setting became more efficient: we find a persistent gap between the relative wages and productivities of both the high-skilled and older workers. Firms who entered the market after the transition set wages more efficiently than older firms.
Restoration of films affected by partial color artefacts

In this paper we present a novel restoration algorithm for a special type of film artefacts resulting mainly from film emulsion melting and the vinegar syndrome. We have devised the algorithm based on the observation that the affected areas did not lose their contents entirely. Rather, one of the film layers still preserves some of the original image structure. This artefact behaviour is exploited for both identifying and restoring these artefacts. The algorithm is validated by showing some results on real case examples.
Point source detection and extraction from simulated Planck time-ordered data using optimal adaptive filters

Wavelet-related techniques have proven useful in the processing and analysis of one- and two-dimensional data sets (spectra in the former case, images in the latter). In this work we apply adaptive filters, introduced in a previous work, to optimize the detection and extraction of point sources from a one-dimensional array of time-ordered data such as the one that will be produced by the future 30-GHz LFI28 channel of the ESA Planck mission. At a 4σ detection level, 224 sources over a flux of 0.88 Jy are detected with a mean relative error (in absolute value) of 21 per cent and a systematic bias of −7.7 per cent. The position of the sources in the sky is determined with errors inferior to the size of the pixel. The catalogue of detected sources is complete at fluxes ≥4.3 Jy. The number of spurious detections is less than 10 per cent of the true detections. We compared the results with the ones obtained by filtering with a Gaussian filter and a Mexican Hat Wavelet of width equal to the scale of the sources. The adaptive filter outperforms the other filters in all considered cases. We conclude that optimal adaptive filters are well suited to detect and extract sources with a given profile embedded in a background of known statistical properties. In the Planck case, they could be useful to obtain a real-time preliminary catalogue of extragalactic sources, which would have a great scientific interest, e.g. for follow-up observations.
Discrimination of movement imagery EEG based on AR and SVM

In the Brain-computer interface, classification and recognition technology plays an important role, especially the EEG classification and recognition for the movement imagery. In this paper, we use a new type of sensors to collect EEG signals. According to imagine the movement of left or right hand to identify two types of thinking, we proposed a new recognition method based on AR(auto-regressive) and SVM (support vector machine). In the identification process uses different kernel functions to classify comparison test. Compared to the traditional method based on support vector machine and Bayes, the correct rate has been greatly improved, and verifies the effectiveness of the method.
3-Aryl-1-phenyl-1H-pyrazole derivatives as new multitarget directed ligands for the treatment of Alzheimer's disease, with acetylcholinesterase and monoamine oxidase inhibitory properties

A series of 3-aryl-1-phenyl-1H-pyrazole derivatives was synthesized in good yield and assayed in vitro as inhibitors of the mice acetylcholinesterase (AChE) and two goat liver monoamine oxidase (MAO) isoforms, MAO-A and MAO-B. Most of the compounds demonstrated a good AChE and selective MAO-B inhibitory activities in the nanomolar or low micromolar range. N-((3-(4-chlorophenyl)-1-phenyl-1H-pyrazole-4-yl) methylene) benzenamine (3e, pIC50 = 4.2) and N-((4-fluorophenyl)-1-phenyl-1H-pyrazole-4-yl) methylene) methanamine (3f, pIC50 = 3.47) were the most potent AChE and highly selective MAO-B inhibitors respectively. Structure activity relationships showed that chloro derivatives were more effective AChE inhibitors as compared to fluoro derivatives while reverse trend was observed in MAO-B inhibitory activity. With the aid of modeling studies, potential binding orientations as well as interactions of the compounds in the AChE and MAO-B active sites were examined.
Adaptive contention access suspension in IEEE 802.15.3 MAC

In IEEE 802.15. 3 MAC, CSMA/CA is used in contention periods (CPs) to send commands. The brief occurrences of CPs cause bursty channel access, thus conventional models based on Poisson arrivals and saturation assumptions are no longer applicable. In this paper, we model CP access in each superframe as a contention resolution problem by applying a frame aggregation strategy for efficient frame transmissions in CPs. Insight gained from this problem formulation motivates us to propose a novel Adaptive CP Suspend (ACS) scheme that is easily implemented using a CP Counter (CPC) at the piconet controller (PNC). The CPC counts down in each idle slot and resets with the appropriate contention windows size after each collision. When the CPC reaches zero, which implies the completion of the contention resolution process, the PNC can safely suspend the remaining CP and devices (DEVs) can go into SLEEP mode to save power. Simulation results show that ACS effectively adapts to changes in channel traffic, substantially shortening the effective region in a CP in which all active DEVs continue to sense the channel, and significantly reducing the system energy cost by allowing DEVs to turn off their radios during the suspended parts of the CPs.
Robust character recognition using adaptive feature extraction

This paper describes an adaptive feature extraction method that exploits category specific information to overcome both image degradation and deformation. When recognizing multiple fonts, geometric features such as directional information of strokes are often used but they are weak against the deformation and degradation that appear in videos and natural scenes. To tackle these problems, the proposed method estimates the degree of deformation and degradation of an input pattern by comparing the input pattern and the template of each category as category specific information. This estimation enables us to compensate the aspect ratio associated with shape and the degradation in feature values. Recognition experiments using characters extracted from videos show that the proposed method is superior to the conventional alternatives in resisting deformation and degradation.
An Attribute-Centre Based Decision Tree Classification Algorithm

— Decision tree algorithms have very important place at classification model of data mining. In literature, algorithms use entropy concept or gini index to form the tree. The shape of the classes and their closeness to each other some of the factors that affect the performance of the algorithm. In this paper we introduce a new decision tree algorithm which employs data (attribute) folding method and variation of the class variables over the branches to be created. A comparative performance analysis has been held between the proposed algorithm and C4.5.
MAURO CAMINATI Knowledge Growth, Complexity and the Returns to R&D

This paper is concerned with the way in which R&D activity in the technological and scientific domains feeds back into the dimension, the hierarchic structure and the complexity of knowledge search spaces. The discussion sets the stage for a critical evaluation of recent contributions trying to identify foundations for the existence of laws of returns to R&D. JEL classification: O3, D83. I whish to thank Carlo Zappia for helpful comments. This paper is the first output of an ongoing research on structural change and technological progress carried out at Siena University under the national project on Growth and Distribution (prot. 2002131335_008) financed by Siena University and the Italian MIUR: COFIN 2002. Mauro Caminati, Dipartimento di Economia Politica, Università degli Studi di Siena
The orthologous Tbx transcription factors Omb and TBX2 induce epithelial cell migration and extrusion in vivo without involvement of matrix metalloproteinases

The transcription factors TBX2 and TBX3 are overexpressed in various human cancers. Here, we investigated the effect of overexpressing the orthologous Tbx genes Drosophila optomotor-blind (omb) and human TBX2 in the epithelium of the Drosophila wing imaginal disc and observed two types of cell motility. Omb/TBX2 overexpressing cells could move within the plane of the epithelium. Invasive cells migrated long-distance as single cells retaining or regaining normal cell shape and apico-basal polarity in spite of attenuated apical DE-cadherin concentration. Inappropriate levels of DE-cadherin were sufficient to drive cell migration in the wing disc epithelium. Omb/TBX2 overexpression and reduced DE-cadherin-dependent adhesion caused the formation of actin-rich lateral cell protrusions. Omb/TBX2 overexpressing cells could also delaminate basally, penetratingthe basal lamina, however, without degradation of extracellular matrix. Expression of Timp, an inhibitor of matrix metalloproteases, blocked neither intraepithelial motility nor basal extrusion. Our results reveal an MMP-independent mechanism of cell invasion and suggest a conserved role of Tbx2-related proteins in cell invasion and metastasis-related processes.
The Vertica Analytic Database: C-Store 7 Years Later

This paper describes the system architecture of the Vertica Analytic Database (Vertica), a commercialization of the design of the C-Store research prototype. Vertica demonstrates a modern commercial RDBMS system that presents a classical relational interface while at the same time achieving the high performance expected from modern "web scale" analytic systems by making appropriate architectural choices. Vertica is also an instructive lesson in how academic systems research can be directly commercialized into a successful product.
COMPARISON OF AERODYNAMIC DESIGN METHODOLOGIES FOR MORPHING UAV WINGS

This paper details two different methodologies for the aerodynamic design of a novel Unmanned Aerial Vehicle (UAV) rectangular wing. The first approach is a one-step optimization process with just one morphing capability: wing-twist morphing, where the sections are twisted to apply the optimum loading distribution over the wing. This is a standard approach for single-objective wing design. This methodology has the advantage of following a simple logic and of being relatively rapid. The second approach is a two-step optimization process that considers two types of morphing mechanisms: camber morphing and wing-twist morphing. The wing is generated via cambering the baseline section in order to apply the correct loading distribution and it is then twisted to further optimize its performance. This twostep methodology incorporates changes in wing-twist and wing-camber; it is slower than the one-step type, but it significantly increases the design-space. This paper demonstrates that different methodologies for aerodynamic design can increase wing efficiency by taking advantage of morphing wing capabilities. The resulting wings provide improved performance when compared against a baseline wing design. Between the two wings, the one generated with the two-steps optimization methodology shows better performance: lower drag; delayed separation; lower design angle of attack. ∗Email: aciarella@ara.co.uk AIAC-2013-000 Ciarella, Andrea
Identifying an interaction site between MutH and the C-terminal domain of MutL by crosslinking, affinity purification, chemical coding and mass spectrometry

To investigate protein–protein interaction sites in the DNA mismatch repair system we developed a crosslinking/mass spectrometry technique employing a commercially available trifunctional crosslinker with a thiol-specific methanethiosulfonate group, a photoactivatable benzophenone moiety and a biotin affinity tag. The XACM approach combines photocrosslinking (X), in-solution digestion of the crosslinked mixtures, affinity purification via the biotin handle (A), chemical coding of the crosslinked products (C) followed by MALDI-TOF mass spectrometry (M). We illustrate the feasibility of the method using a single-cysteine variant of the homodimeric DNA mismatch repair protein MutL. Moreover, we successfully applied this method to identify the photocrosslink formed between the single-cysteine MutH variant A223C, labeled with the trifunctional crosslinker in the C-terminal helix and its activator protein MutL. The identified crosslinked MutL-peptide maps to a conserved surface patch of the MutL C-terminal dimerization domain. These observations are substantiated by additional mutational and chemical crosslinking studies. Our results shed light on the potential structures of the MutL holoenzyme and the MutH–MutL–DNA complex.
A Rough Set Model for Software Defect Prediction

High assurance software requires extensive and expensive assessment. Many software organizations frequently do not allocate enough resources for software quality. We research the defect detectors focusing on the data sets of software defect prediction. A rough set model is presented to deal with the attributes of data sets of software defect prediction in this paper. Appling this model to the most famous public domain data set created by the NASA's metrics data program shows its splendid performance.
QUANTUM COMPUTATION BASED PROBABILITY DENSITY FUNCTION ESTIMATION

Signal processing techniques will lean on blind methods in the near future, where no redundant, resource allocating information will be transmitted through the channel. To achieve a proper decision, however, it is essential to know at least the probability density function (PDF), which to estimate is classically a time consumpting and/or less accurate hard task that may make decisions to fail. This paper describes the design of a quantum assisted PDF estimation method also by way of an example, which promises to achieve the exact PDF by proper setting of parameters in a very rapid way.