Miracle-dz/UniFAR-FTUs huggingface dataset:
Fair Pricing of Life Insurance Participating Policies with a Minimum Interest Rate Guaranteed

Abstract In this paper we analyse, in a contingent-claims framework, one of the most common life insurance policies sold in Italy during the last two decades. The policy, of the endowment type, is initially priced as a standard one, given a mortality table and a technical interest rate. Subsequently, at the end of each policy year, the insurance company grants a bonus, which is credited to the mathematical reserve and depends on the performance of a special investment portfolio. More precisely, this bonus is determined in such a way that the total interest rate credited to the insured equals a given percentage (participation level) of the annual return on the reference portfolio and anyway does not fall below the technical rate (minimum interest rate guaranteed, henceforth). Moreover, if the contract is paid by periodical premiums, it is usually stated that the annual premium is adjusted at the same rate of the bonus, and thus the benefit is also adjusted in the same measure. In such policy the variables controlled by the insurance company (control-variables, henceforth) are the technical rate, the participation level and, in some sense, the riskiness of the reference portfolio measured by its volatility. However, as it is intuitive, not all sets of values for these variables give rise to a fair contract, i.e. to a contract priced consistently with the usual assumptions on financial markets and, in particular, with no-arbitrage. We derive then necessary and sufficient conditions under which each control-variable is determined by a fair pricing of the contract, given the remaining two ones.
Arterial distensibility in children and teenagers: normal evolution and the effect of childhood vasculitis

Background: Polyarteritis nodosa is a necrotising vasculitis of the medium sized and small muscular arteries. The inflammatory and subsequent reparative processes may alter the arterial mechanical properties. The effect of vasculitic damage on arterial distensibility has never been explored however. Aim: To determine the normal values and the effect of childhood vasculitis on arterial distensibility in children and teenagers. Methods: Distensibility of the brachioradial arterial segment was studied using pulse wave velocity (PWV ∝1/√distensibility), in 13 children with polyarteritis nodosa at a median age of 11.8 (range 4.9–16) years. As a control group, 155 healthy schoolchildren (6–18 years, 81 boys) were studied. PWV was assessed using a photoplethysmographic technique; blood pressure was measured by an automatic sphygmomanometer (Dinamap). Data from patients were expressed as z scores adjusted for age and compared to a population mean of 0 by a single sample t test. Determinants of PWV in normal children were assessed by univariate and multivariate linear regression analyses. Results: Age, height, weight, and systolic blood pressure correlated individually with the brachioradial PWV. Multivariate analysis identified age as the only independent determinant. Ten of the patients were in clinical remission, while three had evidence of disease activity at the time of study. The PWV in the patient group as a whole was significantly greater than those in healthy children (mean z score +0.99). Raised C reactive protein concentration (>2 mg/dl) in the three patients with active disease was associated with a higher PWV when compared to those in remission (z score +2.78 v +0.45). The diastolic blood pressure of the patients was higher than those of the controls (z score +1.04) while the systolic pressure was similar (z score −0.36). Conclusions: PWV in the brachioradial arterial segment increases gradually during childhood independent of body weight, height, mass, and blood pressure. Increased PWV, and hence decreased distensibility, in this peripheral arterial segment occurs in polyarteritis nodosa and is amplified during acute inflammatory exacerbation.
A Search in the Forest : Efficient Algorithms for Parsing and Machine Translation based on Packed Forests A DISSERTATION PROPOSAL in Computer and Information Science

Many problems in Natural Language Processing (NLP) involves an efficient search for the best derivation over (exponentially) many candidates. For example, a parser aims to find the best syntactic tree for a given sentence among all derivations under a grammar, and a machine translation (MT) decoder explores the space of all possible translations of the source-language sentence. In these cases, the concept of packed forest provides a compact representation of huge search spaces by sharing common sub-derivations, where efficient algorithms based on Dynamic Programming (DP) are possible. Building upon the hypergraph formulation of forests and well-known 1-best DP algorithms, this dissertation develops fast and exact k-best DP algorithms on forests, which are orders of magnitudes faster than previously used methods on state-of-theart parsers. We also show empirically how the improved output of our algorithms has the potential to improve results from parse reranking systems and other applications. We then extend these algorithms to approximate search when the forests are too big for exact inference. We discuss two particular instances of this new method, forest rescoring for MT decoding, and forest reranking for parsing. In both cases, our methods perform orders of magnitudes faster than conventional approaches. In the latter, faster search also leads to better learning, where our approximate decoding makes whole-Treebank discriminative training practical and results in an accuracy better than any previously reported systems trained on the Treebank. Finally, we discuss the work to be completed, which are mainly further investigations of forest reranking, and its applications to sequence labeling, dependency parsing, and other problems such as machine translation.
Cerebrospinal Fluid and Serum Β eta Secretase Activities in Alzheimer ' s Disease

Cerebrospinal Fluid and Serum Βeta Secretase Activities in Alzheimer's Disease Erdem YAKA, Şermin GENÇ, Leyla İYİLİKÇİ, Görsev YENER Dokuz Eylül Üniversitesi Tıp Fakültesi, Nöroloji Anabilim Dalı, İzmir, Türkiye Dokuz Eylül Üniversitesi Tıp Fakültesi, Sağlık Bilimleri Enstitüsü Sinir Bilimleri Anabilim Dalı, İzmir, Türkiye Dokuz Eylül Üniversitesi Tıp Fakültesi, Anesteziyoloji ve Reanimasyon Anabilim Dalı, İzmir, Türkiye
Dimensionality Reduction using GA-PSO

The feature selection process can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in acceptable classification accuracy. In this paper, we propose a combination of genetic algorithms (GAs) and particle swarm optimization (PSO) for feature selection. The K-nearest neighbor (K-NN) method with leave-one-out cross-validation (LOOCV) serves as an evaluator for the GAs and the PSO. The proposed method is applied to five classification problems taken from the literature. Experimental results show that our method simplifies features effectively and obtains a higher classification accuracy compared to other feature selection methods.
Convolutive Bounded Component Analysis Algorithms for Independent and Dependent Source Separation

Bounded component analysis (BCA) is a framework that can be considered as a more general framework than independent component analysis (ICA) under the boundedness constraint on sources. Using this framework, it is possible to separate dependent as well as independent components from their mixtures. In this paper, as an extension of a recently introduced instantaneous BCA approach, we introduce a family of convolutive BCA criteria and corresponding algorithms. We prove that the global optima of the proposed criteria, under generic BCA assumptions, are equivalent to a set of perfect separators. The algorithms introduced in this paper are capable of separating not only the independent sources but also the sources that are dependent/correlated in both component (space) and sample (time) dimensions. Therefore, under the condition that the sources are bounded, they can be considered as extended convolutive ICA algorithms with additional dependent/correlated source separation capability. Furthermore, they have potential to provide improvement in separation performance, especially for short data records. This paper offers examples to illustrate the space-time correlated source separation capability through a copula distribution-based example. In addition, a frequency-selective Multiple Input Multiple Output equalization example demonstrates the clear performance advantage of the proposed BCA approach over the state-of-the-art ICA-based approaches in setups involving convolutive mixtures of digital communication sources.
Extracellular Matrix and Aberrant Signaling in Lung Carcinoma: Role of Fibronectin in the Control of Human Lung Carcinoma Cell Growth,Apoptosis and Resistance to Therapy

Despite recent advances in understanding the molecular biology of lung carcinoma and the introduction of multiple new chemotherapeutic agents for its treatment, its dismal five-year survival rate (<15%) has not changed substantially. The lack of advancements in this area reflects the limited knowledge available concerning the factors that promote oncogenic transformation and proliferation of carcinoma cells in the lung. Tumor growth and invasion are not only the result of malignant transformation, but also depend on environmental influences from their surrounding stroma, local growth factors, and systemic hormones. In particular, the composition of the extracellular matrix is believed to affect malignant behavior in vivo. This document reviews information that implicates the matrix glycoprotein fibronectin in regulation of lung carcinoma cell proliferation, apoptosis and resistance to therapy. Fibronectin is highly expressed in chronic lung disorders where most lung carcinomas are identified. Data available to date indicate that by binding to specific integrin receptors expressed on tumor cells, fibronectin stimulates a number of intracellular signals implicated in the pathobiology of lung carcinogenesis including GTPases, mitogen-activated protein kinases, and the PI3-Kinase/Akt/mTOR pathway. Targeting fibronectin and integrin-mediated signals in tumor cells represents a promising target for the development of effective anti-cancer strategies.
Thumbs-Up: 3D Spatial Thumb-Reachable Space for One-Handed Thumb Interaction on Smartphones

People very often use mobile devices with one hand to free the second hand for other tasks. In such cases, the thumb of the hand holding the device is the only available input finger, making multi-touch interactions impossible. Complicating interaction further, the screen area that can be reached with the thumb while holding the device is limited, which makes distant on-screen areas inaccessible. Motivated by emerging portable object tracking technologies, we explore how spatial mid-air thumb-gestures could potentially be used in combination with on-screen touch input to facilitate one-handed interaction. From a user study we identify the 3D thumb-reachable space when holding a smartphone. We call this space "Thumbs-Up". This space extends up to 74 mm above the screen, making it possible to create interactions for the thumb of the hand holding the smartphone. We furthermore demonstrate how such Thumbs-Up techniques, when combined with on-screen interaction, can extend the input vocabulary in one-handed situations.
Stochastic simulation model for nonstationary time series using an autoregressive wavelet decomposition: Applications to rainfall and temperature

A time series simulation scheme based on wavelet decomposition coupled to an autoregressive model is presented for hydroclimatic series that exhibit band‐limited low‐frequency variability. Many nonlinear dynamical systems generate time series that appear to have amplitude‐ and frequency‐modulated oscillations that may correspond to the recurrence of different solution regimes. The use of wavelet decomposition followed by an autoregressive model of each leading component is explored as a model for such time series. The first example considered is the Lorenz‐84 low‐order model of extratropical circulation, which has been used to illustrate how chaos and intransitivity (multiple stable solutions) can lead to low‐frequency variability. The central England temperature (CET) time series, the NINO3.4 series that is a surrogate for El Nino–Southern Oscillation, and seasonal rainfall from Everglades National Park, Florida, are then modeled with this approach. The proposed simulation model yields better results than a traditional linear autoregressive (AR) time series model in terms of reproducing the time‐frequency properties of the observed rainfall, while preserving the statistics usually reproduced by the AR models.
A Generic Anonymization Framework for Network Traffic

Lack of trust is one of the main reasons for the limited cooperation between different organizations. The privacy of users is of paramount importance to administrators and organizations, which are reluctant to cooperate between each other and exchange network traffic traces. The main reasons behind reluctance to exchange monitored data are the protection of the users' privacy and the fear of information leakage about the internal infrastructure. Anonymization is the technique to overcome this reluctance and enhance the cooperation between different organizations with the smooth exchange of monitored data. Today, several organizations provide network traffic traces that are anonymized by software utilities or ad-hoc solutions that offer limited flexibility. The result of this approach is the creation of unrealistic traces, inappropriate for use in evaluation experiments. Furthermore, the need for fast on-line anonymization has recently emerged as cooperative defense mechanisms have to share network traffic. Our effort focuses on the design and implementation of a generic and flexible anonymization framework that provides extended functionality, covering multiple aspects of anonymization needs and allowing fine-tuning of privacy protection level. The proposed framework is composed by an anonymization application programming interface (AAPI). The performance results show that AAPI outperforms existing tools, while offering significantly more anonymization primitives.
Bridging the Gap: Incorporating Work and Learning Using Cooperative Learning Environments

Summary Although lifelong learning is a well accepted concept, it is still not a prominent part of everyday business. A common problem is the lack of knowledge transfer from learning to work. Learning and working are falsely considered as separate activities within different contexts. In addition, while most work in today’s dynamic business world is done by teams, learning often focuses, in theory as well as in practise, on the individual learner, thus neither exploiting the potential benefit of cooperation nor helping learners to acquire the necessary cooperation skills. In the CLear (Cooperative Learning) project at GMD-IPSI, cooperative environments are developed which support such learning processes in the form of a seamless transition between work and learning. Our interdisciplinary approach focuses on task-oriented learning of small teams of adult learners and takes into consideration different learning dimensions such as synchronous and asynchronous learning, distributed and co-located learning, and individual and group learning This paper addresses bridging the current gap between working and learning based upon the CLear project. The potential inadequacies of traditional learning techniques in meeting the demands of today’s learning needs are examined. In addition, we explain in more detail the cooperative learning prototype developed for the CLear project in terms of its technical aspects and innovativeness.
An energy-aware method for the joint recognition of activities and gestures using wearable sensors

This paper presents an energy-aware method for recognizing time series acceleration data containing both activities and gestures using a wearable device coupled with a smartphone. In our method, we use a small wearable device to collect accelerometer data from a user's wrist, recognizing each data segment using a minimal feature set chosen automatically for that segment. For each collected data segment, if our model finds that recognizing the segment requires high-cost features that the wearable device cannot extract, such as dynamic time warping for gesture recognition, then the segment is transmitted to the smartphone where the high-cost features are extracted and recognition is performed. Otherwise, only the minimum required set of low-cost features are extracted from the segment on the wearable device and only the recognition result, i.e., label, is transmitted to the smartphone in place of the raw data, reducing transmission costs. Our method automatically constructs this adaptive processing pipeline solely from training data.
Particle Learning of Gaussian Process Models for Sequential Design and Optimization

We develop a simulation-based method for the online updating of Gaussian process regression and classification models. Our method exploits sequential Monte Carlo to produce a fast sequential design algorithm for these models relative to the established MCMC alternative. The latter is less ideal for sequential design since it must be restarted and iterated to convergence with the inclusion of each new design point. We illustrate some attractive ensemble aspects of our SMC approach, and show how active learning heuristics may be implemented via particles to optimize a noisy function or to explore classification boundaries online. Supplemental material, including an R package, is available online.
Detections of Arterial Wall in Sonographic Artery Images Using Dual Dynamic Programming

We propose a novel dual dynamic programming (DDP) technique for detecting intimal and adventitial layers of the common carotid artery of the B-mode sonographic images. This method embeds the anatomic knowledge into its structure so that the robustness against the speckles is increased. Moreover, it inherits the property of getting the optimal solution as the traditional dynamic programming (TDP). Our experimental study shows that the DDP technique achieves a detection performance comparable to manual tracing achieved by physicians. The results demonstrate that it has the potential to perform qualitatively better than applying TDP twice in intimal and adventitial layer detection on sonographic B-mode images.
LOCALIZING SOUND IN ROOMS

Department of Cognitive and Neural Systems and Biomedical Engineering Boston University, 677 Beacon St., Boston, MA 02215 Email: shinn@cns.bu. edu Ph: 617-353-5764 FAX: 617-353-7755 INTRODUCTION Relatively little psychoacoustic work has examined how realistic echoes and reverberation affect spatial auditory perception. Within psychoacoustics, echoes and reverberation are generally thought to 1) cause little degradation in directional perception (as suggested by studies of the "precedence effect"; e.g., see Litovsky, Colburn, Yost & Guzman, 1999) and 2) improve distance perception (by some essentially unknown mechanism; e.g., see Mershon & King, 1975).
A Novelty Approach for Image Data Hiding Based on Frequency Watermark

This paper presents in detail an analysis of the ability of data hiding capabilities. According to the human visual features, this paper uses edge degree which can be computed by Log points, and combines distributed evenly degrees with sigmoid function which is adopted to describe bright hiding capability, and proposes an effective method to measure the data hiding capability. Moreover, this paper implements embedding and distilling watermark based on the frequency modulation. Using the idea of frequency modulation that belongs to communication engineering, and bringing up "frequency modulation watermark" which different to traditional watermark technique, we constitute base band signal by select the intermediate frequency coefficients of image piece which has strong data conceals ability, then, embedding and picking up watermark according to the idea of frequency modulation. This kind of watermark technique can give attention to invisibleness and robustness, and realize blind examination efficiently The experiments show that the technique has the properties of combing invisibility and robustness as well as achieving efficient blind detection.
In vitro efficacy of ganciclovir, cidofovir, penciclovir, foscarnet, idoxuridine, and acyclovir against feline herpesvirus type-1.

OBJECTIVE To establish the in vitro efficacy of 4 novel drugs (ie, ganciclovir, cidofovir, penciclovir, and foscarnet) against feline herpesvirus type-1 (FHV-1) and compare their antiviral efficacy with that of acyclovir and idoxuridine. SAMPLE POPULATION Cultured Crandell-Reese feline kidney (CRFK) cells and FHV-1 strain 727 PROCEDURE For each drug, antiviral effect was estimated by use of conventional plaque-reduction assays, and inhibitory concentration 50 (IC50; drug concentration at which plaque numbers were reduced by 50% relative to the number of plaques for nontreated control wells) was calculated. To determine whether observed antiviral effects were related to alterations in the number or viability of CRFK cells, cytotoxicity assays were performed at 1, 2, and 10 times the median IC50 for each antiviral drug. RESULTS Median IC50 for each drug was as follows: ganciclovir, 5.2 microM; cidofovir, 11.0 microM; penciclovir, 13.9 microM; foscarnet, 232.9 microM; idoxuridine, 4.3 microM; and acyclovir, 57.9 microM. Obvious changes in morphologic characteristics, confluence, or viability of CRFK cells were not observed at concentrations up to and including 2 times the IC50 for each drug. CONCLUSIONS AND CLINICAL RELEVANCE In vitro efficacy of idoxuridine and ganciclovir against FHV-1 was approximately equivalent and about twice that of cidofovir and penciclovir. Foscarnet appeared to be comparatively ineffective. Given the reasonable clinical efficacy of idoxuridine in cats infected with FHV-1, clinical trials of ganciclovir, cidofovir, and penciclovir or their prodrug forms appear to be warranted.