nils-herrmann/clean_scirepeval huggingface dataset:
Target Tracking with a Flexible UAV Cluster Array
Venue: 2016 IEEE Globecom Workshops (GC Wkshps)

Unmanned aerial vehicle (UAV) cluster applications, for tasks such as target localisation and tracking, are required to collect and utilise the data received on "flexible" sensor arrays, where the sensors, i.e. UAVs in this scenario, have time variant positions. In this paper, using a parametric channel model, a UAV cluster mobility model and a kinematic model of the targets, an extended Kalman based state space model is proposed that tracks the unknown UAV positions and target parameters snapshot by snapshot. Simulation studies illustrating the tracking capabilities of the proposed technique have been presented.
The Impact of Information on Doctors' Attitudes Toward Generic Drugs
Venue: Inquiry a journal of medical care organization, provision and financing

The objective of this study is to assess the impact of information on doctors' attitudes and perceptions toward generics. A cross sectional survey based on a specially designed 21 item questionnaire was conducted. The survey involved doctors of different specialties working in a public hospital in Greece. The analysis includes descriptive and inferential statistics, reliability and validity tests, as well as structural equation modeling to evaluate the causal model. Statistical analysis was accomplished by using SPSS 20 and Amos 20. A total of 134 questionnaires out of 162 were received, providing a response rate of 82.71% A number of significant associations were found between information and perceptions about generic medicines with demographic characteristics. It seems that the provision of quality information on generic drugs influences doctors' attitudes and prescription practices toward generic drugs. This is not a static process but a rather dynamic issue involving information provision policies for strengthening the proper doctors' attitudes toward generic drugs.
A review on the state of art of Internet of Things

The Internet of Things is fast growing technology with business opportunities and risks. It is confluence of wireless networks, internet and computing. IoT connects the physical objects like vehicles, buildings and other devices with embedded intelligent sensors and enables these objects to exchange and collect data. The domains where IoT is becoming popular are smart cities, e health, smart grids, e commerce, smart transportation, and e commerce etc. The embedded and wearable computing will have greater impact in providing services in wide range of applications by 2020[1] The architecture of IoT is incorporated with the latest technologies of communication protocols, intelligent sensor and RFID. The security and privacy issues of IoT are crucial as it connects large number devices. In this article we analyze a state of art review of IoT with regard to technologies, protocols, application issues.
A Framework for Scientific Paper Retrieval and Recommender Systems
Venue: ArXiv

Information retrieval (IR) and recommender systems (RS) have been employed for addressing search tasks executed during literature review and the overall scholarly communication lifecycle. Majority of the studies have concentrated on algorithm design for improving the accuracy and usefulness of these systems. Contextual elements related to the scholarly tasks have been largely ignored. In this paper, we propose a framework called the Scientific Paper Recommender and Retrieval Framework (SPRRF) that combines aspects of user role modeling and user interface features with IR/RS components. The framework is based on eight emergent themes identified from participants feedback in a user evaluation study conducted with a prototype assistive system. 119 researchers participated in the study for evaluating the prototype system that provides recommendations for two literature review and one manuscript writing tasks. This holistic framework is meant to guide future studies in this area.
Thermal oxidation of vinyl ester and unsaturated polyester resins

The thermal oxidative ageing of vinyl ester and unsaturated polyester was studied at temperatures ranging from 120 to 160 degC and oxygen pressures ranging from 0.02 to 2.0 MPa. The oxidation of both materials was shown to generate anhydrides detected by FTIR spectroscopy, the origin of which being the oxidation of CH2 group in a position of ester, and significant mass loss. According to FTIR study, vinyl ester was shown to be more oxidizable than unsaturated polyesters but this feature is counterbalanced by a lower volatile yield. The thickness of oxidized layer in diffusion limited oxidation regime was hence observed to be higher in Unsaturated Polyester (ca 600 mm) than in Vinyl Ester (ca 200 mm) at 160 degC and seems not affected by the presence of high content of fillers.
The effect of impurities in reactive diluents prepared from lignin model compounds on the properties of vinyl ester resins

Vinyl ester resins (VERs) often contain high concentrations of a petroleum based reactive diluent, such as styrene. Reactive diluents that can be derived from lignin, including phenyl methacrylate (PM) 2 methoxyphenyl methacrylate (MG) and 4 propyl 2 methoxyphenyl methacrylate (M4PG) were synthesized and investigated as potential styrene replacements. A commercial VER was blended with each lignin derived reactive diluent, and styrene, in 7:3 and 1:1 weight ratios and cured to 94% based on near IR spectral analysis. The substituents on the aromatic ring of the lignin derived reactive diluent are shown to have small effects on viscosity, thermogravimetric, and thermomechanical properties of the cured resins, where, in general, the smaller the reactive diluent, the greater the glass transition temperature (Tg) and the lower the viscosity. Increasing purity of the reactive diluents through chromatographic separations substantially increases the Tg and degradation temperatures of the resins. The results suggest that PM, MG, and M4PG are effective bio based reactive diluent replacements for styrene.
Massage therapy research review.
Venue: Complementary therapies in clinical practice

In this review, massage therapy has been shown to have beneficial effects on varying conditions including prenatal depression, preterm infants, full term infants, autism, skin conditions, pain syndromes including arthritis and fibromyalgia, hypertension, autoimmune conditions including asthma and multiple sclerosis, immune conditions including HIV and breast cancer and aging problems including Parkinson's and dementia. Although many of the studies have involved comparisons between massage therapy and standard treatment control groups, several have compared different forms of massage (e.g. Swedish versus Thai massage) and different active therapies such as massage versus exercise. Typically, the massage therapy groups have experienced more positive effects than the control or comparison groups. This may relate to the massage therapy providing more stimulation of pressure receptors, in turn enhancing vagal activity and reducing cortisol levels. Some of the researchers have assessed physical, physiological and biochemical effects, although most have relied exclusively on self report measures. Despite these methodological problems and the dearth of research from the U.S. the massage therapy profession has grown significantly and massage therapy is increasingly practiced in traditional medical settings, highlighting the need for more rigorous research.
The Impact of Massage Therapy on Function in Pain Populations A Systematic Review and Meta Analysis of Randomized Controlled Trials: Part I, Patients Experiencing Pain in the General Population
Venue: Pain medicine

Pain is multi dimensional and may be better addressed through a holistic, biopsychosocial approach. Massage therapy is commonly practiced among patients seeking pain management; however, its efficacy is unclear. This systematic review and meta analysis is the first to rigorously assess the quality of massage therapy research and evidence for its efficacy in treating pain, function related and health related quality of life outcomes across all pain populations.  Key databases were searched from inception through February 2014. Eligible randomized controlled trials were assessed for methodological quality using SIGN 50 Checklist. Meta analysis was applied at the outcome level. A diverse steering committee interpreted the results to develop recommendations.  Sixty high quality and seven low quality studies were included in the review. Results demonstrate massage therapy effectively treats pain compared to sham [standardized mean difference (SMD) .44] no treatment (SMD 1.14) and active (SMD 0.26) comparators. Compared to active comparators, massage therapy was also beneficial for treating anxiety (SMD 0.57) and health related quality of life (SMD 0.14)  Based on the evidence, massage therapy, compared to no treatment, should be strongly recommended as a pain management option. Massage therapy is weakly recommended for reducing pain, compared to other sham or active comparators, and improving mood and health related quality of life, compared to other active comparators. Massage therapy safety, research challenges, how to address identified research gaps, and necessary next steps for implementing massage therapy as a viable pain management option are discussed.
On numerical homogenization of shale gas transport
Venue: J. Comput. Appl. Math.

In this paper, we study the numerical homogenization for the gas transport in organic rich shale with heterogeneous kerogen distribution. We consider organic rich shale as the domain with two subdomains: inorganic matrix and kerogen. The processes in both regions are described by nonlinear parabolic equations, which take into account the filtration, diffusion, and adsorption. We follow the work of Yucel Akkutlu et?al. (2015) where the authors develop homogenization techniques for the gas transport in organic rich shale. We use the framework of Yucel Akkutlu et?al. (2015) and develop numerical homogenization for two dimensional examples. We discuss local subgrid calculations and the approaches to compute the effective properties numerically. In our methods, the local problems use Dirichlet boundary conditions. We compare the properties of the fine grid reference solution against those of the coarse grid model. Our approaches show a good agreement between macroscopic quantities.
Tourism demand modelling and forecasting using data mining techniques in multivariate time series: a case study in Turkey

In this study multiple linear regression, multilayer perceptron (MLP) regression, and support vector regression (SVR) are used to make multivariate tourism forecasting for Turkey. This paper is a comparative study of data mining techniques based on multivariate regression modelling with monthly data points to forecast tourism demand; it focuses on Turkey. Both MLP and SVR methods are widely employed in the variety forecasting problems. Most of the previous research on tourism forecasting used univariate time series or a limited number of variables with mostly yearly or quarterly, and rarely monthly frequencies. However, the application of data mining techniques for multivariate forecasting in the context of tourism demand has not been widely explored. This paper differs from earlier research in two ways: 1) it proposes multivariate regression modelling with monthly data points to forecast tourism demand; and 2) it focuses on Turkey by using a dataset with the most recently accumulated (between January 1996 and Dec 2013) 67 time series with respect to Turkey and its top 26 major tourism clients. Comparison of forecasting performances in terms of relative absolute error (RAE) and root relative squared error (RRSE) measurements shows that the SVR model, with RAE 12.34% and RRSE 14.02% gives a better performance. The results obtained in this study provide information for researchers interested in applying data mining techniques to tourism demand forecasting and help policy makers, government bodies, investors, and managers for their regularization, planning, and investments by way of accurate tourism demand forecasting.
A survey on data mining techniques applied to energy time series forecasting

Data mining has become an essential tool during the last decade to analyze large 1 sets of data. The variety of techniques it includes and the successful results obtained in 2 many application fields, make this family of approaches powerful and widely used. In 3 particular, this work explores the application of these techniques to time series forecasting. 4 Although classical statistical based methods provides reasonably good results, the result of 5 the application of data mining outperforms those of classical ones. Hence, this work faces 6 two main challenges: i) to provide a compact mathematical formulation of the mainly used 7 techniques, ii) to review the latest works of time series forecasting and, as case study, those 8 related to electricity price and demand markets.
Functionalization and Reduction of Graphene Oxide

The chemistry of graphene oxide (GO) is a growing field of research. The modification of the surface properties of GO is the main goal in application driven research. Successful functionalization protocols must be interpreted in accordance with the chemical structure of the original GO, and therefore, in this chapter, crucial aspects of the chemical structure of GO are introduced first. Next, the thermal and chemical stability of GO is reviewed, followed by introducing wet chemical non covalent and covalent reaction principles. The covalent functionalization of GO requires special attention. When chemical reaction principles, well known from organic chemistry, are applied to GO, it remains challenging to prove the successful accomplishment of reactions by analyzing the as modified GO product. We pay special attention to the reactivity of the edges of defects and provide alternative explanations for interpreting experimental results, where necessary. Next, chemical reduction methods are summarized; special accent is placed on differentiating true chemical reduction from so called "thermal reduction" Several examples for the functionalization of reduced graphene oxide (RGO) are considered next. While discussing GO chemical properties, in parallel with typical GO, we discuss these properties for the oxo functionalized graphene (oxo G1) a type of GO with very low density of structural defects. This sheds additional light on the role of defects in GO chemistry. Finally, additional properties of oxo G1 are introduced. Oxo G1 can act as a compound that enables the controlled chemistry for the design and synthesis of functional materials and devices.
Anonymous Attestation Using the Strong Diffie Hellman Assumption Revisited
Venue: TRUST

Direct Anonymous Attestation (DAA) is a cryptographic protocol for privacy protecting authentication. It is standardized in the TPM standard and implemented in millions of chips. A variant of DAA is also used in Intel's SGX. Recently, Camenisch et al. (PKC 2016) demonstrated that existing security models for DAA do not correctly capture all security requirements, and showed a number of flaws in existing schemes based on the LRSW assumption. In this work, we identify flaws in security proofs of a number of qSDH based DAA schemes and point out that none of the proposed schemes can be proven secure in the recent model by Camenisch et al. (PKC 2016) We therefore present a new, provably secure DAA scheme that is based on the qSDH assumption. The new scheme is as efficient as the most efficient existing DAA scheme, with support for DAA extensions to signature based revocation and attributes. We rigorously prove the scheme secure in the model of Camenisch et al. which we modify to support the extensions. As a side result of independent interest, we prove that the BBS+ signature scheme is secure in the type 3 pairing setting, allowing for our scheme to be used with the most efficient pairing friendly curves.
Quantum Plasmonics
Venue: Proceedings of the IEEE

Quantum plasmonics is an exciting subbranch of nanoplasmonics where the laws of quantum theory are used to describe light matter interactions on the nanoscale. Plasmonic materials allow extreme subdiffraction confinement of (quantum or classical) light to regions so small that the quantization of both light and matter may be necessary for an accurate description. State of the art experiments now allow us to probe these regimes and push existing theories to the limits which opens up the possibilities of exploring the nature of many body collective oscillations as well as developing new plasmonic devices, which use the particle quality of light and the wave quality of matter, and have a wealth of potential applications in sensing, lasing, and quantum computing. This merging of fundamental condensed matter theory with application rich electromagnetism (and a splash of quantum optics thrown in) gives rise to a fascinating area of modern physics that is still very much in its infancy. In this review, we discuss and compare the key models and experiments used to explore how the quantum nature of electrons impacts plasmonics in the context of quantum size corrections of localized plasmons and quantum tunneling between nanoparticle dimers. We also look at some of the remarkable experiments that are revealing the quantum nature of surface plasmon polaritons.
Thermodynamic properties and solidification kinetics of intermetallic Ni7Zr2 alloy investigated by electrostatic levitation technique and theoretical calculations

The thermodynamic properties, including the density, volume expansion coefficient, ratio of specific heat to emissivity of intermetallic Ni7Zr2 alloy, have been measured using the non contact electrostatic levitation technique. These properties vary linearly with temperature at solid and liquid states, even down to the obtained maximum undercooling of 317 K. The enthalpy, glass transition, diffusion coefficient, shear viscosity, and surface tension were obtained by using molecular dynamics simulations. Ni7Zr2 has a relatively poor glass forming ability, and the glass transition temperature is determined as 1026 K. The inter diffusivity of Ni7Zr2 alloy fitted by Vogel Fulcher Tammann law yields a fragility parameter of 8.49, which indicates the fragile nature of this alloy. Due to the competition of increased thermodynamic driving force and decreased atomic diffusion, the dendrite growth velocity of Ni7Zr2 compound exhibits double exponential relationship to the undercooling. The maximum growth velocity is.
Speed Control Based on ESO for the Pitching Axis of Satellite Cameras

The pitching axis is the main axis of a satellite camera and is used to control the pitch posture of satellite cameras. A control strategy based on extended state observer (ESO) is designed to obtain a fast response speed and highly accurate pitching axis control system and eliminate disturbances during the adjustment of pitch posture. First, a sufficient condition of stabilization for ESO is obtained by analyzing the steady state error of the system under step input. Parameter tuning and disturbance compensation are performed by ESO. Second, the ESO of speed loop is designed by the speed equation of the pitching axis of satellite cameras. The ESO parameters are obtained by pole assignment. By ESO, the original state variable observes the motor angular speed and the extended state variable observes the load torque. Therefore, the external load disturbances of the control system are estimated in real time. Finally, simulation experiments are performed for the system on the cases of nonload starting, adding external disturbances on the system suddenly, and the load of system changing suddenly. Simulation results show that the control strategy based on ESO has better stability, adaptability, and robustness than the PI control strategy.
Pitch reduction and traction enhancement of an EV by real time brake biasing and in wheel motor torque control

This paper focuses on pitch control in braking and traction enhancement in acceleration. During braking the vehicle pitches, which greatly determines the ride comfort; on the other hand, during acceleration an optimum value of wheel slip is desired for better traction. In the first part, we control the vehicle pitch of a Fox electric vehicle by real time brake biasing. We begin with determining side view swings arm centre positions as a function of wheel travel for both front and rear suspensions. Next using these instantaneous centres, vehicle pitch point is determined and the mathematical model for vehicle pitching is developed. Finally, a PD controller is developed which minimises vehicle pitch using brake biasing. In the second part, the motor torques are controlled by maintaining a constant wheel slip at which maximum longitudinal force is generated. The results show significant reduction in vehicle pitch and better tracking of desired velocity profile.
Safety and efficacy of repeated injections of botulinum toxin A in peripheral neuropathic pain (BOTNEP) a randomised, double blind, placebo controlled trial
Venue: The Lancet Neurology

Data from previous studies suggest that botulinum toxin A has analgesic effects against peripheral neuropathic pain, but the quality of the evidence is low. We aimed to assess the safety and efficacy of repeated administrations of botulinum toxin A in patients with neuropathic pain.  We did a randomised, double blind, placebo controlled trial at two outpatient clinics in France ( and one in Brazil (Neurological Department, Hospital das Clinicas da FMUSP, Sao Paulo) Patients aged 18 85 years with peripheral neuropathic pain were randomly assigned (1:1) by block randomisation, according to a centralised schedule, to receive two subcutaneous administrations of botulinum toxin A (up to 300 units) or placebo, 12 weeks apart. All patients and investigators were masked to treatment assignment. The primary outcome was the efficacy of botulinum toxin A versus placebo, measured as the change from baseline in self reported mean weekly pain intensity over the course of 24 weeks from the first administration. The primary efficacy analysis was a mixed model repeated measures analysis in the intention to treat population.  Between Oct 2, 2010, and Aug 2, 2013, 152 patients were enrolled, of whom 68 were randomly assigned (34 per group) and 66 (37 [56% men) were included in the primary analysis (34 in the botulinum toxin A group and 32 in the placebo group) Botulinum toxin A reduced pain intensity over 24 weeks compared with placebo (adjusted effect estimate 0*77, 95% CI 0*95 to 0*59; p<0*0001) Pain on injection was the only adverse effect reported, and occurred in 19 (56% participants in the botulinum toxin A group and 17 (53% of those in the placebo group (p=1*0) Severe pain was experienced by ten (29% participants in the botulinum toxin A group and 11 (34% in the placebo group (p=0*8) INTERPRETATION Two administrations of botulinum toxin A, each of which comprised several injections, have a sustained analgesic effect against peripheral neuropathic pain. Several factors, such as the presence of allodynia and a limited thermal deficit, may be useful in predicting treatment response and should be investigated further.  and Fondation CNP (France)