Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance comparison of proximal methods for regression with nonsmooth regularizers on real datasets

First order methods are known to be effective for high-dimensional machine learning problems due to their faster convergence and low per-iteration-complexity. In machine learning, many problems are designed as a convex minimization problem with smooth loss function and non-smooth regularizers. Learning with sparsity-inducing regularizers belongs to this class of problems, where a number of first order methods are already available in the literature of optimization and machine learning theory. Proximal methods also come under the class of first-order methods and lead to better sparse models. In this paper, we discuss three state-of-the-art proximal methods for the problem of regression, when the loss minimization is associated with a sparsity-inducing regularizer. This paper presents for the first time their comparison based on practical convergence rates, prediction accuracy and consumed CPU time on six real datasets.
Cryptanalysis of Short Signature Scheme Without Random Oracles Assumption

This paper presents an attack on a new short signature scheme from bilinear pairing proposed by Dan Boneh et al. at J. Crypt. We show that an attacker can alter the public key of the signer and then can forge the signer’ s signature for any message m. Furthermore, we argue that the well-accepted notion of security for signature schemes, namely existential unforgeability against adaptive chosen-message attacks, is not adequate for the multi-user setting. We firstly define a new notion of security named non-repudiation for the short signature schemes. We believe that the signature scheme, which satisfies non-repudiation, is more secure.
NLOS Identification and Mitigation for UWB Localization Systems

Non-line-of-sight (NLOS) identification and mitigation carries significant importance in wireless positioning systems. In this paper, the authors propose a novel NLOS identification technique based on the multipath channel statistics such as the kurtosis, the mean excess delay spread, and the root mean square delay spread. In particular, the IEEE 802.15. 4a ultrawideband channel models are used as examples and the above statistics are found to be well modeled by log-normal random variables. Subsequently, a joint likelihood ratio test is developed for LOS/NLOS identification. Simulation results show that correct identification can be achieved with over 90% of the realizations for most channel models. A weighted least squares localization algorithm is also developed using the NLOS information, and accuracy gains with respect to a conventional least squares algorithm are demonstrated via Monte-Carlo simulations.
Personality classification and behaviour interpretation: an approach based on feature categories

This paper focuses on recognizing and understanding social dimensions (the personality traits and social impressions) during small group interactions. We extract a set of audio and visual features, which are divided into three categories: intra-personal features (i.e. related to only one participant), dyadic features (i.e. related to a pair of participants) and one vs all features (i.e. related to one participant versus the other members of the group). First, we predict the personality traits (PT) and social impressions (SI) by using these three feature categories. Then, we analyse the interplay be- tween groups of features and the personality traits/social impressions of the interacting participants. The prediction is done by using Support Vector Machine and Ridge Regression which allows to determine the most dominant features for each social dimension. Our experiments show that the combination of intra-personal and one vs all features can greatly improve the prediction accuracy of personality traits and social impressions. Prediction accuracy reaches 81.37% for the social impression named ’Rank of Dominance’. Finally, we draw some interesting conclusions about the relationship between personality traits/social impressions and social features.
The Relation between Fundamental Constants and Particle Physics Parameters

The observed constraints on the variability of the proton to electron mass ratio μ and the fine structure constant α are used to establish constraints on the variability of the Quantum Chromodynamic Scale and a combination of the Higgs Vacuum Expectation Value and the Yukawa couplings. Further model dependent assumptions provide constraints on the Higgs VEV and the Yukawa couplings separately. A primary conclusion is that limits on the variability of dimensionless fundamental constants such as μ and α provide important constraints on the parameter space of new physics and cosmologies.
Inferential Network Analysis with Exponential Random Graph Models

Methods for descriptive network analysis have reached statistical maturity and general acceptance across the social sciences in recent years. However, methods for statistical inference with network data remain fledgling by comparison. We introduce and evaluate a general model for inference with network data, the Exponential Random Graph Model (ERGM) and several of its recent extensions. The ERGM simultaneously allows both inference on covariates and for arbitrarily complex network structures to be modeled. Our contributions are three-fold: beyond introducing the ERGM and discussing its limitations, we discuss extensions to the model that allow for the analysis of non-binary and longitudinally observed networks and show through applications that network-based inference can improve our understanding of political phenomena.
A Short Proof of the Harris–Kesten Theorem

We give a short proof of the fundamental result that the critical probability for bond percolation in the planar square lattice Z2 is equal to 1/2. The lower bound was proved by Harris, who showed in 1960 that percolation does not occur at p = 1/2. The other, more difficult, bound was proved by Kesten, who showed in 1980 that percolation does occur for any p > 1/2. 2000 Mathematics Subject Classification 60K35, 82B43.
On Subjective Trust for Privacy Policy Enforcement in Cloud Computing

The growth of cloud computing over the last few years has created an ecosystem where it is necessary for the clients to transact with cloud service providers even though the cloud service clients may or may not completely trust the provider. There is a need for the provider to acknowledge this subjective trust assessment by each client and provide services based on the trust assessment individually to each client. This paper proposes a policy based approach to the implementation of subjective trust for privacy policy enforcement in a cloud computing environment. We present an abstract model containing computational, storage and monitoring unit with configurable elements and describe algorithms that reflects how a change of trust influences the configuration of the elements. We prototype a storage middleware based on the abstract model and benchmark our system.
CRF Based on LHFS Applied on Sentiment Classification

Sentiment classification has attracted increasing interest from natural language processing. This paper applies CRF(Conditional Random Filed) based on LHFS (Local High-Frequency Strings) method on sentence sentiment analysis. This method can effectively solve ordinal regression problems. In this method, sentences are labeled to determine their polarity, and LHFS method is used to expand the set of sentiment features. Experiments on sentiment classification indicate that the accuracy of CRF model is increased up to 2.1%, with the help of LHFS method, which is much better than that of HMM and MEMM.
Estimation of land surface temperature retrieved from EOS/MODIS in Naqu area over Tibetan Plateau

Using split window algorithms developed by Sobrino,added a sufficient and simple cloud detection process for MODIS L1B data.Then based on land surface classification(land,water,snow ice),retrieved four land surface temperature images for clear sky in Naqu area over Tibetan Plateau in January,April,June and October in 2007,respectively.After that the derived LST was compared with the MODIS daily land surface temperature product and in-situ data from the Coordinated Enhanced Observing Period(CEOP) Asia-Australia Monsoon Project(CAMP) on Tibetan Plateau(CAMP/Tibet). The results showed that the LST derived from the improved Sobrino method was in good accordance with the MODIS product and the average difference between LST and in-situ measurements was only 1.435 K.
On the Estimation of Solar Energetic Particle Injection Timing from Onset Times near Earth

We examine the accuracy of a common technique for estimating the start time of solar energetic particle injection based on a linear fit to the observed onset time versus 1/(particle velocity). This is based on a concept that the first arriving particles move directly along the magnetic field with no scattering. We check this by performing numerical simulations of the transport of solar protons between 2 and 2000 MeV from the Sun to the Earth, for several assumptions regarding interplanetary scattering and the duration of particle injection, and by analyzing the results using the inverse velocity fit. We find that, in most cases, the onset times align close to a straight line as a function of inverse velocity. Despite this, the estimated injection time can be in error by several minutes. Also, the estimated path length can deviate greatly from the actual path length along the interplanetary magnetic field. The major difference between the estimated and actual path lengths implies that the first arriving particles cannot be viewed as moving directly along the interplanetary magnetic field.
Exponential and Power Law Distribution of Contact Duration in Urban Vehicular Ad Hoc Networks

Contact duration between moving vehicles is one of the key metrics in vehicular ad hoc networks (VANETs), that critically influences the design of routing schemes and network throughput. Due to prohibitive costs to collect enough realistic contact records, little experimental work has been conducted to study the contact duration in urban VANETs. In this work, we carry out an extensive experiment involving tens of thousands of operational taxis in Beijing city. Based on studying this newly collected Beijing trace and the existing Shanghai trace, we find an invariant characteristic that there exists a characteristic time point, up to which the contact duration obeys an exponential distribution that includes at least 80% of the whole distribution, while beyond which it decays as a power law one. This property is in sharp contrast to the recent empirical data studies based on human mobility, where the contact duration exhibits a power law distribution. Our observations thus provide fundamental guidelines for the design of new urban VANETs' routing protocols and their performance evaluation.
Bmc Complementary and Alternative Medicine Effect of Exercise Therapy on Lipid Profile and Oxidative Stress Indicators in Patients with Type 2 Diabetes

Background: Yoga has been shown to be a simple and economical therapeutic modality that may be considered as a beneficial adjuvant for type 2 diabetes mellitus. This study investigated the impact of Hatha yoga and conventional physical training (PT) exercise regimens on biochemical, oxidative stress indicators and oxidant status in patients with type 2 diabetes.
Peripheral sensory neuropathy is associated with altered postocclusive reactive hyperemia in the diabetic foot

Objective This study examined whether the presence of peripheral sensory neuropathy or cardiac autonomic deficits is associated with postocclusive reactive hyperemia (reflective of microvascular function) in the diabetic foot. Research design and methods 99 participants with type 2 diabetes were recruited into this cross-sectional study. The presence of peripheral sensory neuropathy was determined with standard clinical tests and cardiac autonomic function was assessed with heart rate variation testing. Postocclusive reactive hyperemia was measured with laser Doppler in the hallux. Multiple hierarchical regression was performed to examine relationships between neuropathy and the peak perfusion following occlusion and the time to reach this peak. Results Peripheral sensory neuropathy predicted 22% of the variance in time to peak following occlusion (p<0.05), being associated with a slower time to peak but was not associated with the magnitude of the peak. Heart rate variation was not associated with the postocclusive reactive hyperemia response. Conclusions This study found an association between the presence of peripheral sensory neuropathy in people with diabetes and altered microvascular reactivity in the lower limb.
NUTRITIONAL VALUE OF CRUDE GLYCERIN FOR NONRUMINANTS

In 2004, the United States consumed 140 billion gallons of gasoline and 40 billion gallons of diesel for on-road transportation (Annual Energy Outlook, 2007; http://www.eia.doe.gov/oifa/aeo/). In an effort to reduce dependence on petroleum-based fuel products and reduce their negative impact on the environment (Hill et al., 2006), production of biofuels from renewable energy sources has experienced explosive growth. Like the rapid expansion of ethanol production (projected 4.8 billion gallon production in 2006, Iowa Corn Promotion Board, 2007; http://www.iowacorn.org), biodiesel production has also rapidly expanded, albeit a smaller production volume, to its current production level of 250 million gallons (Figure 1; National Biodiesel Board, 2007; http://www.nbb.org).
An Extinction Map and Color-Magnitude Diagram for the Globular Cluster NGC 3201

Differential EV-I variations of up to ∼0.2 mag on a scale of arcminutes across NGC 3201 are presented in the form of an extinction map. This map, created by calculating average EV-I values for stars in small subregions of the field with respect to a fiducial region, greatly improves the appearance of the color-magnitude diagram of the cluster. We describe how we implemented this technique in detail with our data for NGC 3201. A comparison between our map and that of the same region extracted from the COBE DIRBE reddening maps published by Schlegel, Finkbeiner, & Davis in 1998 (hereafter SFD) displays larger scale similarities between the two maps, as well as smaller scale features that show up in our map but not in the SFD map. Several methods of determining an EV-I zero point to add to our differential extinction map are presented. Isochrone fitting proved to be the most successful one, but it produces an average EV-I for the cluster that is smaller by ∼1.5 σ than previously published values. Finally, our results seem to support the statement by Arce & Goodman that the SFD maps overestimate the reddening in regions of high extinction.
Effect of Tannin-Binding Agents (Polyethylene Glycol and Polyvinylpyrrolidone) Supplementation on In Vitro Gas Production Kinetics of Some Grape Yield Byproducts

The effects of polyethylene glycol (PEG) and polyvinylpyrrolidone (PVP) on in vitro gas production characteristics, organic matter digestibility (OMD), and metabolizable energy (ME) contents of some grape yield byproducts were investigated. The gas production was recorded after 2, 4, 6, 8, 12, 16, 24, 36, and 48 h of incubation. The gas production profiles in triplicate fitted with equation Y = A (1 – e−ct). The data was analyzed using completely randomized design. Total phenol (TP) and total tannin (TT) contents were highest for raisin waste (RW). The TP content (g/kg DM) ranged from 30.1 in grape pomace (GP) to 96.3 in RW, which also had the higher TT (72.1 g/kg DM). The potential gas production (a + b) of DGB, GP, and RW were 239.43, 263.49, and 208.22 mL/g DM, respectively. In the absence of PEG and PVP, rate constant of gas production (c) for GP was highest among the feedstuffs (0.1073 mL/h), but in presence of PEG or PVP, RW had highest fraction (c) among the feedstuffs. Addition of PEG and PVP inactivated effects of tannins and increased gas production, ME, NE1, OMD, and VFA in grape yield byproducts. Addition of PEG and PVP could overcome adverse effects of tannins on nutrient availability as indicated by gas production parameters.
Social networking services as a facilitator for scientists' sharing activities

Abstract Understanding and structuring the use of social software by scientists is of high importance in modern research and education – new ways of cooperation and knowledge sharing leads to new ways of work for researchers in both, higher education and enterprises. The possibilities of social networking services provides means for open discourse and offers easier ways to make scientific and educational resources available to the knowledge community. Within this paper, we create a research model and study knowledge sharing and technology acceptance related influence factors to share knowledge in the form of artefacts. These artefacts consist of open science and open educational resources. With our study we will validate the model of sharing influences and understand which factors are most relevant for scientists in IS discipline to share scientific and educational information through social networking services. Through the research, an improved understanding for the use of social software for globally distributed and open scientific communication is obtained. Keywords: Social Networking Services, Open Educational Resources, Open Science Resources, Technology Acceptance, Knowledge Sharing.
Opportunistic rover science: finding and reacting to rocks, clouds and dust devils

The goal of the Onboard Autonomous Science Investigation System (OASIS) project at NASA's Jet Propulsion Laboratory (JPL) is to evaluate, and autonomously act upon, science data gathered by in-situ spacecraft, such as planetary landers and rovers. Using the FIDO rover in the Mars yard at JPL, we have successfully demonstrated a closed loop system test of the rover acquiring image data, finding rocks in the image, analyzing rock properties and identifying rocks that merit further investigation. When the system on the rover alerts the rover to take additional measurements of interesting rocks, the planning and scheduling component determines if there are enough resources to meet this additional science data request. The rover is then instructed to either turn toward the rock, or to actually move closer to the rock to take an additional, close up, picture. In addition to these hardware integration successes, the OASIS team has also continued its autonomous science research by collaboratively working with other scientists and technologists to identify and react to other scientific phenomena - such as clouds and dust devils. Prototype dust devil and cloud detection algorithms were delivered to an infusion task which has refined the algorithms specifically for Mars exploration rovers (MER) and is integrating the code into the next release of MER flight software
A single chip system for ECG feature extraction

This paper proposes an on-line system for feature extraction from ECG signal. The QRS detector, RR interval calculator, heart rate calculator and additional modules are developed in VHDL code and embedded in a single FPGA chip. The overall design has a low hardware occupation, 1838 LEs, and minimal number of setting parameters, only two, sampling and clock rates. The achieved accuracy is 97.5%. As such, it is very suitable for embedding in wearable health care systems, portable instruments and telemedicine devices. The methodology for QRS detection, system architecture and preliminary testing results are presented.
Preparation of magnetic mesoporous silica nanoparticles as a multifunctional platform for potential drug delivery and hyperthermia

Abstract We report the preparation of magnetic mesoporous silica (MMS) nanoparticles with the potential multifunctionality of drug delivery and magnetic hyperthermia. Carbon-encapsulated magnetic colloidal nanoparticles (MCN@C) were used to coat mesoporous silica shells for the formation of the core-shell structured MMS nanoparticles (MCN@C/mSiO2), and the rattle-type structured MMS nanoparticles (MCN/mSiO2) were obtained after the removal of the carbon layers from MCN@C/mSiO2 nanoparticles. The morphology, structure, magnetic hyperthermia ability, drug release behavior, in vitro cytotoxicity and cellular uptake of MMS nanoparticles were investigated. The results revealed that the MCN@C/mSiO2 and MCN/mSiO2 nanoparticles had spherical morphology and average particle sizes of 390 and 320 nm, respectively. The MCN@C/mSiO2 nanoparticles exhibited higher magnetic hyperthermia ability compared to the MCN/mSiO2 nanoparticles, but the MCN/mSiO2 nanoparticles had higher drug loading capacity. Both MCN@C/mSiO2 and MCN/mSiO2 nanoparticles had similar drug release behavior with pH-controlled release and temperature-accelerated release. Furthermore, the MCN@C/mSiO2 and MCN/mSiO2 nanoparticles showed low cytotoxicity and could be internalized into HeLa cells. Therefore, the MCN@C/mSiO2 and MCN/mSiO2 nanoparticles would be promising for the combination of drug delivery and magnetic hyperthermia treatment in cancer therapy.
LMMSE Receivers for DS-CDMA Systems in Frequency-Selective Fading Channels

| The linear minimum mean squared error (LMMSE) criterion can be used to obtain near-far resistant single-user receivers in direct-sequence code-division multiple-access (DS-CDMA) systems. The standard version (postcombining) of the LMMSE receiver minimizes the mean squared error (MSE) between the lter output and the actual transmitted data sequence. Since the detector depends on the channel coeecients of all users, it cannot be implemented adaptively in fading channels due to severe convergence problems. A modiied criterion for deriving LMMSE receivers in fading channels is presented. The modiied (precombining) LMMSE receiver is independent from users' complex channel coeecients, and it effectively converts the pathological Rayleigh fading channel to an equivalent xed AWGN channel from the detector updating perspective. The precombining LMMSE receiver leads to blind adaptive implementations. Some alternative blind adaptive receivers are reviewed and their performance in frequency-selective fading channels is addressed. Since the blind adaptive implementations require explicit information on multipath delays, delay estimation issue will also be considered. The blind adaptive interference suppression methods are applied furthermore to the residual interference suppression in parallel interference cancellation multiuser receivers.
Phonological Representation: Beyond Abstract Versus Episodic

Phonological representations capture information about individual word forms and about the general characteristics of word forms in a language. To support the processing of novel word forms as well as familiar word forms in novel contexts, an abstract level of representation is needed in which many phonetic details and contextual features are disregarded. At the same time, evidence has accumulated that such details are retained in memory and used in processing individual words and indexical features of language. Taken together, these results mean that a hybrid model of phonological representation is needed. The abstract level supports generalizations based on lexical type statistics and fast adaptation to communicative requirements through the reuse of existing categories. A richly detailed level of representation is implicated in word-specific phonetic patterns, the detailed dynamics of regular sound changes, and active associations of phonetic patterns with gender, age, and dialect.