Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing and Balancing Load in Fully Distributed P2P File Sharing Systems

A peer-to-peer file sharing system includes a lookup and a content distribution protocol. Very efficient peer-to-peer protocols exist for content distribution, but efficient indexing is still an open problem. Numerous work on structured overlay networks such as distributed hash tables offer a promising framework. However, balancing the load of publishing, storing indexes and answering request still remains a challenging task. We sketch a general architecture framework for solving these problems in the case of a file sharing application. Our design goals include reducing the work of file providers (they should not bare all the publishing process) and enabling keyword searching based on the assumption that few words are associated with each file.
New four-phase generation circuits for low-voltage charge pumps

A new four-phase clock generator for the four-phase charge pumping circuits for very low supply voltages using 0.5 /spl mu/m double poly CMOS technology to generate high boosted voltages is presented. With the new clock generator, the ten-stage charge pump can efficiently pump to 9 V at supply voltage of 1 V.
Instant immunity through chemically programmable vaccination and covalent self-assembly

The ability to instantly create a state of immunity as achieved in the passive transfer of hyperimmune globulin has had a tremendous impact on public health. Unlike passive immunization, active immunization, which is the foundation of vaccinology, is an anticipatory strategy with inherent limitations. Here we show that elements of active and passive immunization can be combined to create an effective chemistry-driven approach to vaccinology. Reactive immunization was used to create a reservoir of covalent polyclonal antibodies in 3 mouse strains that were subsequently engrafted with syngeneic CT26 colon or B16F10 melanoma tumors. Upon administration of designed integrin αvβ3 and αvβ5 adapter ligands, the induced covalent polyclonal antibodies self-assembled with the adapter ligands and the animals mounted an instant, chemically programmed, polyclonal response against the implanted tumors. Significant therapeutic responses were observed without recourse to adjuvant therapy. The chemically programmed immune responses were driven by antibody-dependent cellular cytotoxicity and complement-directed cytotoxicity. We suggest that this type of chemistry-driven approach to vaccinology is underexplored and may provide routes to vaccines to protect against diseases that have proven intractable to biology-driven vaccine approaches.
Metal-mask configurable RF front-end circuits

This paper describes metal-mask configurable RF circuits using a base circuit fabric that can be configured for various wireless applications using only upper metal and via layers. This front-end circuit fabric achieves a wide range of configurability (e.g., operating center frequency) and is essentially applicable for any IC technology. The prototype RF front-end circuit fabric was designed to be configurable for GPS at 1.5 GHz, W-CDMA at 2.1 GHz and WLAN at 5 GHz in a 0.25-/spl mu/m 47-GHz f/sub T/ SiGe BiCMOS process. The upper three metal and via layers are the only application-specific layers for the three applications. The front-end circuits draw 10.5, 9.5, and 8.5 mA from a 2.5-V supply, respectively, at 1.5, 2.1, and 5 GHz while providing a noise figure of 2.5, 2.8, and 4.5 dB, conversion gain of 24.6, 24.2, and 12 dB, and IIP3 of -8, -9, and -4 dBm, respectively.
The influence of a yoga exercise program for young adults with intellectual disabilities

Background: Individuals with intellectual disabilities (ID) have an increased risk of obesity and are significantly less likely to engage in physical activity compared to their nondisabled peers. A growing body of research supports the physical and mental health benefits of yoga. While the benefits of yoga have been studied across a host of populations with varying ages and physical disabilities, no studies could be identified investigating the benefits of yoga for young adults with ID. Aims: This study investigated the impact of participating in yoga classes on the amount of exercise behavior and perception of physical exertion when compared to non-structured exercise sessions between two young adults with ID in a post-secondary education setting. Materials and Methods: A single subject multiple baseline research design was implemented across two young adults with mild ID to determine the effects of a yoga exercise class on frequency of exercise behavior and perception of physical exertion when compared to non-structured exercise sessions. Partial interval recording, the Eston-Parfitt curvilinear rating of perceived exertion scale, and the physical activity enjoyment scale were implemented to collect data on dependent variables and consumer satisfaction during each non-structured exercise session and each yoga class. Results: indicated that percentage of exercise behavior and perceived exertion levels during yoga group exercise sharply increased with large effect sizes when compared to non-structured exercise sessions.
The automatic news transcription system: ANTS, some real time experiments

This paper presents the recent development of ANTS, the Automatic News Transcription System of LORIA. This system was designed in the framework of ESTER, the French broadcast radio news transcription task evaluation. After describing its different components and some segmentation and recognition results on the ESTER database, we present a number of experiments focusing on the real-time version of ANTS. We evaluate the system with different number of Gaussians, sizes of vocabulary and decoder settings. The non real time version of ANTS yields an overall error rate of 36 % that can be compared to 44.5 % for the real time version.
Fuzzy risk assessment of mortality after coronary surgery using combination of adaptive neuro‐fuzzy inference system and K‐means clustering

In this paper, a fuzzy expert system based on adaptive neuro‐fuzzy inference system (ANFIS) is introduced to assess the mortality after coronary bypass surgery. In preprocessing phase, the attributes were reduced using a univariant analysis in order to make the classifier system more effective. Prognostic factors with a p‐value of less than 0.05 in chi‐square or t‐student analysis were given to inputs ANFIS classifier. The correct diagnosis performance of the proposed fuzzy system was calculated in 824 samples. To demonstrate the usefulness of the proposed system, the study compared the performance of fuzzy system based on ANFIS method through the binary logistic regression with the same attributes. The experimental results showed that the fuzzy model (accuracy: 96.4%; sensitivity: 66.6%; specificity: 97.2%; and area under receiver operating characteristic curve: 0.82) consistently outperformed the logistic regression (accuracy: 89.4%; sensitivity: 47.6%; specificity: 89.4%; and area under receiver operating characteristic curve: 0.62). The obtained classification accuracy of fuzzy expert system was very promising with regard to the traditional statistical methods to predict mortality after coronary bypass surgery such as binary logistic regression model.
Bivariate random effects models for meta-analysis of comparative studies with binary outcomes: Methods for the absolute risk difference and relative risk

Multivariate meta-analysis is increasingly utilised in biomedical research to combine data of multiple comparative clinical studies for evaluating drug efficacy and safety profile. When the probability of the event of interest is rare, or when the individual study sample sizes are small, a substantial proportion of studies may not have any event of interest. Conventional meta-analysis methods either exclude such studies or include them through ad hoc continuality correction by adding an arbitrary positive value to each cell of the corresponding 2 × 2 tables, which may result in less accurate conclusions. Furthermore, different continuity corrections may result in inconsistent conclusions. In this article, we discuss a bivariate Beta-binomial model derived from Sarmanov family of bivariate distributions and a bivariate generalised linear mixed effects model for binary clustered data to make valid inferences. These bivariate random effects models use all available data without ad hoc continuity corrections, and accounts for the potential correlation between treatment (or exposure) and control groups within studies naturally. We then utilise the bivariate random effects models to reanalyse two recent meta-analysis data sets.
Image emphasis based on integration of high frame-rate images by new gradient-based motion estimation method

We study a imaging system for reconstructing high spatial resolution image using high frame-rate images obtained by an image sensor. To apply high frame-rate images, it is assumed that the temporal correlation between motion vectors is high. We have previously proposed a motion estimation method based on the high accurate spatial gradients by predicting the motion vectors in the current frame from those of the previous frame. In this paper, we propose an improved method that uses two contiguous frames to accurately estimate the spatial gradients. The target pixel position is then shifted according to the predicted motion vector. We evaluate the proposed method and confirm its effectiveness, and demonstrate the increased spatial resolution using high frame-rate images as an application of the proposed motion estimation.
Escape analysis in the context of dynamic compilation and deoptimization

In object-oriented programming languages, an object is said to escape the method or thread in which it was created if it can also be accessed by other methods or threads. Knowing which objects do not escape allows a compiler to perform aggressive optimizations.This paper presents a new intraprocedural and interprocedural algorithm for escape analysis in the context of dynamic compilation where the compiler has to cope with dynamic class loading and deoptimization. It was implemented for Sun Microsystems' Java HotSpot™ client compiler and operates on an intermediate representation in SSA form. We introduce equi-escape sets for the efficient propagation of escape information between related objects. The analysis is used for scalar replacement of fields and synchronization removal, as well as for stack allocation of objects and fixed-sized arrays. The results of the interprocedural analysis support the compiler in inlining decisions and allow actual parameters to be allocated on the caller stack.Under certain circumstances, the Java HotSpot™ VM is forced to stop executing a method's machine code and transfer control to the interpreter. This is called deoptimization. Since the interpreter does not know about the scalar replacement and synchronization removal performed by the compiler, the deoptimization framework was extended to reallocate and relock objects on demand.
Evolutionary games with random number of interacting players applied to access control

We study access games within a large population of mobiles that interfere with each other through many local interactions. Each local interaction involves a random number of mobiles. The games are not necessarily reciprocal as the set of mobiles causing interference to a given mobile may differ from the set of those suffering from its interference. We model and study this using the theory of evolutionary games which we extend to cover a random number of players.
Geometry-driven Scheme for Geocast Routing in Mobile Ad Hoc Networks

This paper considers the problem of geocasting in mobile ad hoc networks. Geocasting, a variation on the notion of multicasting, is a mechanism to deliver messages of interest to all nodes within a certain geographical target region. Although several geocasting protocols have already been proposed for mobile ad hoc networks, with the goal of achieving an efficient message delivery, most of these algorithms consider a "single" target region only and therefore multiple transmissions should be initiated separately by the message source when more than one target regions need to receive the same geocast messages. This causes significant performance degradation, especially as the number of geocast regions increase. To solve this problem, we propose a novel scheme driven by geometry, named GGP (geometry-driven geocasting protocol). In this scheme, the geometric concept of "Fermat point" is utilized to determine the optimal junction point among multiple geocast regions from the source node, and hence to reduce the overhead of message delivery, while maintaining a high delivery ratio
Query Merging: Improving Query Subscription Processing in a Multicast Environment

This paper introduces techniques for reducing data dissemination costs of query subscriptions in a multicast environment. The reduction is achieved by merging queries with overlapping, but not necessarily equal, answers. The paper formalizes the query-merging problem and introduces a general framework and cost model for evaluating merging. We prove that the problem is NP-hard and propose exhaustive algorithms and three heuristic algorithms: the pair merging algorithm, the directed search algorithm, and the clustering algorithm. We develop a simulator, which uses geographical queries as a representative example for evaluating the different heuristics and show that the performance of our heuristics is close to optimal.
Induction machine design methodology for self-sensing: Balancing saliencies and power conversion properties

Zero to low speed, flux or rotor position self-sensing techniques rely on the interaction of saliencies (asymmetries) with an injected signal or special switching pattern in the inverter to produce a response which contains information about the location of the saliency. In this paper three types of deterministic spatial rotor position saliencies are introduced into an induction machine. The saliencies were created by modulating the 1) rotor bridge opening width, 2) rotor bridge opening height, and 3) rotor bridge opening fill. The influence of saliency geometric design variables on self-sensing and power conversion properties is determined using a design of experiments and response surface methodology. An example induction machine design, which maximizes self-sensing properties while preserving power conversion abilities, is presented. Modulation of the rotor bridge fill appears to be the least desirable saliency type. Both rotor bridge opening width and height modulations can be used successfully but the rotor bridge opening width modulation requires extra simulations to characterize self-sensing properties.
The ArtiPhon Task at Evalita 2016

English. Despite the impressive results achieved by ASR technology in the last few years, state-of-the-art ASR systems can still perform poorly when training and testing conditions are different (e.g., different acoustic environments). This is usually referred to as the mismatch problem. In the ArtiPhon task at Evalita 2016 we wanted to evaluate phone recognition systems in mismatched speaking styles. While training data consisted of read speech, most of testing data consisted of single-speaker hypoand hyper-articulated speech. A second goal of the task was to investigate whether the use of speech production knowledge, in the form of measured articulatory movements, could help in building ASR systems that are more robust to the effects of the mismatch problem. Here I report the result of the only entry of the task and of baseline systems. Italiano. Nonostante i notevoli risultati ottenuti recentemente nel riconoscimento automatico del parlato (ASR) le prestazioni dei sistemi ASR peggiorano significativamente in quando le condizioni di testing sono differenti da quelle di training (per esempio quando il tipo di rumore acustico è differente). Un primo gol della ArtiPhon task ad Evalita 2016 è quello di valutare il comportamento di sistemi di riconoscimento fonetico in presenza di un mismatch in termini di registro del parlato. Mentre il parlato di training consiste di frasi lette ad un velocita; di eloquio “standard”, il parlato di testing consiste di frasi sia iperche ipo-articolate. Un secondo gol della task è quello di analizzare se e come l’utilizzo di informazione concernente la produzione del parlato migliora l’accuratezza dell’ASR e in particolare nel caso di mismatch a livello di registri del parlato. Qui riporto risultati dell’unico sistema che è stato sottomesso e di una baseline.
Precise RNAi-mediated silencing of metabolically active proteins in the defence secretions of juvenile leaf beetles

Allomones are widely used by insects to impede predation. Frequently these chemical stimuli are released from specialized glands. The larvae of Chrysomelina leaf beetles produce allomones in gland reservoirs into which the required precursors and also the enzymes are secreted from attached gland cells. Hence, the reservoirs can be considered as closed bio-reactors for producing defensive secretions. We used RNA interference (RNAi) to analyse in vivo functions of proteins in biosynthetic pathways occurring in insect secretions. After a salicyl alcohol oxidase was silenced in juveniles of the poplar leaf beetles, Chrysomela populi, the precursor salicyl alcohol increased to 98 per cent, while salicyl aldehyde was reduced to 2 per cent within 5 days. By analogy, we have silenced a novel protein annotated as a member of the juvenile hormone-binding protein superfamily in the juvenile defensive glands of the related mustard leaf beetle, Phaedon cochleariae. The protein is associated with the cyclization of 8-oxogeranial to iridoids (methylcyclopentanoid monoterpenes) in the larval exudates made clear by the accumulation of the acylic precursor 5 days after RNAi triggering. A similar cyclization reaction produces the secologanin part of indole alkaloids in plants.
Predicting emergency department inpatient admissions to improve same-day patient flow.

OBJECTIVES The objectives were to evaluate three models that use information gathered during triage to predict, in real time, the number of emergency department (ED) patients who subsequently will be admitted to a hospital inpatient unit (IU) and to introduce a new methodology for implementing these predictions in the hospital setting. METHODS Three simple methods were compared for predicting hospital admission at ED triage: expert opinion, naïve Bayes conditional probability, and a generalized linear regression model with a logit link function (logit-linear). Two months of data were gathered from the Boston VA Healthcare System's 13-bed ED, which receives approximately 1,100 patients per month. Triage nurses were asked to estimate the likelihood that each of 767 triaged patients from that 2-month period would be admitted after their ED treatment, by placing them into one of six categories ranging from low to high likelihood. Logit-linear regression and naïve Bayes models also were developed using retrospective data and used to estimate admission probabilities for each patient who entered the ED within a 2-month time frame, during triage hours (1,160 patients). Predictors considered included patient age, primary complaint, provider, designation (ED or fast track), arrival mode, and urgency level (emergency severity index assigned at triage). RESULTS Of the three methods considered, logit-linear regression performed the best in predicting total bed need, with a receiver operating characteristic (ROC) area under the curve (AUC) of 0.887, an R(2) of 0.58, an average estimation error of 0.19 beds per day, and on average roughly 3.5 hours before peak demand occurred. Significant predictors were patient age, primary complaint, bed type designation, and arrival mode (p < 0.0001 for all factors). The naïve Bayesian model had similar positive predictive value, with an AUC of 0.841 and an R(2) of 0.58, but with average difference in total bed need of approximately 2.08 per day. Triage nurse expert opinion also had some predictive capability, with an R(2) of 0.52 and an average difference in total bed need of 1.87 per day. CONCLUSIONS Simple probability models can reasonably predict ED-to-IU patient volumes based on basic data gathered at triage. This predictive information could be used for improved real-time bed management, patient flow, and discharge processes. Both statistical models were reasonably accurate, using only a minimal number of readily available independent variables.
Real-Time Phase Vocoder Manipulation by Runner's Pace

This paper presents a method for using a runner’s pace for real-time control of the time-scaling facility of a phase vocoder, resulting in the automated synchronization of an audio track tempo to the generated control signal. The increase in usage of portable music players during exercise has given rise to the development of new personal exercise aids, most notably the Nike+iPod system, which relies on embedded sensor technologies to provide kinematic workout statistics. There are also systems that select songs based on the measured step frequency of a runner. The proposed system also uses the pace of a runner, but this information is used to change the tempo of the music.
Phase-error compensation through multiframe blind deconvolution

In this paper the multiframe blind deconvolution method [Schulz, 1993] for the identification and correction of turbulence-induced phase aberrations in a ground-based telescope is extended to include the gains, backgrounds, and biases inherent in many charge-coupled device (CCD) cameras. In addition, an application of this method to real telescope data is described.
Consumer spending in the gaming industry: evidence of complementary demand in casino and online venues

Brick and mortar gambling stakeholders have scrutinized Internet gambling sites over concern that online operators may serve as substitutes for their products. In some cases, this has led to regulatory protection to prevent or restrict entry by online providers. However, many industry observers have remarked that the two gambling modalities may serve different consumers/consumer needs, or even serve as complementary goods. Policymakers, who look to gambling as an important source of tax revenue, must determine how expansion of Internet gambling will affect overall economic welfare. Using self-reported consumer gambling behaviour data from the United Kingdom, the net effect of Internet-based gambling activity on land-based demand is estimated in this study. A robust complementary (positive) relationship between online and offline gambling is found, using ordinary least squares, two-stage least squares, and two-part modeling techniques. These particular findings suggest that economic concerns around the cannibalization of traditional gambling industries should be reconsidered, and provide support for prior research showing that Internet based firms can be complementary to brick and mortar businesses.
Enhancement of IR Images using Homomorphic Filtering in Fast Discrete Curvelet Transform (FDCT)

This paper presents an efficient model for enhancement of Infrared images. The proposed method is employing homomorphic filtering in the Fast Discrete Curvelet Transform (FDCT). It based on mixing the advantages of FDCT for representing curves and clarifying features on it with Homomorphic filtering which is an efficient method for enhancing the appearance of IR images. Also, we investigate the influence of FDCT coefficients on the Infrared images. The proposed method gives good results with respect to objective and subjective measurements when using only the first and last FDCT coefficients. General Terms Infrared images Enhancement.