nils-herrmann/clean_scirepeval huggingface dataset:
Decrease of Rotavirus Gastroenteritis to a Low Level Without Resurgence for Five Years After Universal RotaTeq Vaccination in Finland
Venue: The Pediatric infectious disease journal

Universal rotavirus (RV) vaccination with RotaTeq was introduced into National Immunization Programme (NIP) of Finland in September 2009. We have previously reported the reduction of RV gastroenteritis (GE) cases in the first 2 years after RV vaccination in NIP in Finland.  In Tampere University Hospital, a 2 year survey of acute GE (AGE) in children was conducted before NIP in the years 2006 to 2008. This was followed by a similar prospective survey in years 2009 to 2011 and now extended to years 2012 to 2014. Stool samples from children examined in the hospital for AGE were analyzed by real time polymerase chain reaction assays for RV and norovirus, and positive samples were typed by sequencing.  The proportion of RVGE of all AGE cases decreased from 52% (421 of 809 cases) in pre NIP years to 26% (86 of 330 cases) in post NIP years 2009 to 2011 falling to 12% (40 of 347 cases) in 2012 and 2014. The hospitalizations for RVGE were reduced by 90% and the outpatient clinic visits also by 90% in 2012 to 2014, compared with pre NIP year; all AGE cases were reduced by 59% Norovirus was a major causative agent of AGE in the post NIP period, accounting for 34% of the cases in 2009 to 2011 and 29% in 2012 to 2014.  RV vaccination in NIP has led to a major reduction of RVGE cases seen in hospital with no resurgence in 5 years after NIP. A high coverage of RV vaccination will maintain RV activity at a low level but not eliminate wild type RV circulation.
Aspect Term and Opinion Target Extraction from Web Product Reviews using Semi markov Conditional Random Fields with Word Embeddings as Features
Venue: WIMS

Descriptions and reviews for products abound on the web and characterise the corresponding products through their aspects. Extracting these aspects is essential to better understand these descriptions, e.g. for comparing or recommending products. Current pattern based aspect extraction approaches focus on flat patterns extracting flat sets of adjective noun pairs. Aspects also have crucial importance on sentiment classification in which sentiments are matched with aspect level expressions. A preliminary step in both aspect extraction and aspect based sentiment analysis is to detect aspect terms and opinion targets. In this paper, we propose a sequential learning approach to extract aspect terms and opinion targets from opinionated documents. For the first time, we use semi markov conditional random fields for this task and we incorporate word embeddings as features into the learning process. We get comparative results on the benchmark datasets for the subtask of aspect term extraction in SemEval 2014 Task 4 and the subtask of opinion target extraction in SemEval 2015 Task 12. Our results show that word embeddings improve the detection accuracy for aspect terms and opinion targets.
A Hybrid Method of Domain Lexicon Construction for Opinion Targets Extraction Using Syntax and Semantics
Venue: Journal of Computer Science and Technology

Opinion targets extraction of Chinese microblogs plays an important role in opinion mining. There has been a significant progress in this area recently, especially the method based on conditional random field (CRF) However, this method only takes lexicon related features into consideration and does not excavate the implied syntactic and semantic knowledge. We propose a novel approach which incorporates domain lexicon with groups of syntactical and semantic features. The approach acquires domain lexicon through a novel way which explores syntactic and semantic information through Partof Speech, dependency structure, phrase structure, semantic role and semantic similarity based on word embedding. And then we combine the domain lexicon with opinion targets extracted from CRF with groups of features for opinion targets extraction. Experimental results on COAE2014 dataset show the outperformance of the approach compared with other well known methods on the task of opinion targets extraction.
Unpacking the innovation ecosystem construct: Evolution, gaps and trends

The innovation ecosystem construct has emerged as a promising approach in the literature on strategy, innovation and entrepreneurship. It draws upon former business ecosystem literature. However, the term innovation ecosystem has been employed in very polysemic and sometimes competing ways. Many adjectives used with reference to innovation ecosystems render the consolidation of the construct more difficult which its characteristics, boundaries and relation with other, to some extent competing, constructs, such as supply chain and value chain are. To clarify concepts, to identify trends and research opportunities, we conducted a systematic literature review from 1993 to 2016, with a hybrid methodology including bibliometric and content analysis. Besides highlighting the most influential papers and exhaustively discussing the innovation ecosystem concept and its variations, we identify a turning point in the literature, the transition from business ecosystem to innovation ecosystem. Business ecosystem relates mainly to value capture, while innovation ecosystem relates mainly to value creation. We conclude by describing six research streams in innovation ecosystem: industry platform x innovation ecosystem; innovation ecosystem strategy, strategic management, value creation and business model; innovation management; managing partners; the innovation ecosystem lifecycle; innovation ecosystem and new venture creation. These streams lead us to propose opportunities for further research to solidify the innovation ecosystem concept.
A Lyapunov function based optimal hybrid power system controller for improved transient stability

In this paper, an intelligent power system stabilizer based on a stable and optimal hybrid learning based adaptive control architecture is proposed which is evolved from approximate dynamic programming technique. The hybrid learning controller is based on two algorithms: (a) A reinforcement learning neural network controller implemented by adaptive critic design (ACD) and (b) A model reference adaptive controller (MRAC) The proposed method uses a novel value priority architecture for integrating these two algorithms. The designed ACD approximates nonlinear functional dynamics of the power system and interacts with the MRAC that adapts based on parametric changes. The value priority scheme developed based on a softmax network generates a hybrid control signal derived from a Lyapunov stability function that evaluates identification, performance, and stability of each controller. The overall hybrid control algorithm ensures convergence to an optimal control solution without using an explicit model of the system and at the same time ensures overall system stability. Theoretical results are validated by simulation studies for electric generator stabilization on a 2 area 5 generator power system and as a wide area controller on IEEE 68 bus system.
Learning adaptive reaching skills with nonlinear dynamical systems directly from human demonstrations
Venue: 2016 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO)

In this work, we first discuss details about a novel motion planning approach for robot point to point reaching tasks called stable estimator of dynamical systems (SEDS) A human operator first demonstrates reaching movements several times, and Gaussian Mixture Model and Gaussian Mixture Regression are used to roughly encode human demonstrations through a first order ordinary differential equation. Then based on Lyapunov Stability Theorem, a constrained nonlinear optimization problem is formulated to iteratively refine the previously learned differential model and SEDS is derived. Since during human demonstrations, the velocity is usually quite low which heavily restricts the kinetic capability of the robot, and sometimes we expect the robot to move more fast, such as to catch flying objects and to avoid fast moving obstacles. Therefore, it is extremely significant to develop a method to control the velocity and duration of the robot movement. In this paper, we define a nonlinear function based on the distance between the robot and the target to adjust the velocity of the robot. Experiments have been conducted in simulation environments to verify three properties of the proposed method, namely global asymptotical stability, adaptation to spatial perturbations and velocity controllability.
Adaptive back stepping tracking control of robot manipulators considering actuator dynamic
Venue: 2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)

An adaptive back stepping controller based on least squares support vector machine (LS SVM) is developed for precision positioning of robot manipulators that can compensate for dynamic friction and uncertainty in manipulator dynamics and actuator dynamics. Firstly, using cross validation algorithm to get LS_SVM initial parameters based on offline learning. Secondly, introducing the error of LS SVM into the adaptive law of the back stepping control and designing the compound disturbance observer system by adjusting LS SVM. Last, choosing Lyapunov function in turn based on the compound disturbance observer and the system error and designing the self adaptive control system based on state feedback and compound disturbance observer. The Lyapunov stability theory is used to prove stability of the proposed control system. The simulation results show that the proposed method has stronger robustness, smaller tracking error and faster response speed than the conventional PD controller.
The formation of diffusive staircases
Venue: Journal of Fluid Mechanics

Radko's recent article ( 2016, pp. 147 170) entitled Thermohaline layering in dynamically and diffusively stable shear flows, is slated to become a seminal reference in the field of fluid dynamics. It proposes an elegant solution to the long standing question of why thermohaline staircases form in the high latitude oceans. Equally importantly, it provides a rare and interesting example of how two physical processes that are both strongly stable when considered individually, can trigger a linear instability when they interact.
Enhanced IoT Aware Online Shopping System
Venue: 2016 12th International Conference on Signal Image Technology Internet Based Systems (SITIS)

In online business, it is important to construct sale web pages offering attractive services for popular products in order to improve page access as well as purchase rates. Moreover, online shop owners need to hold various types of sales frequently throughout the year to keep customers coming back. Also, online shopping systems have to adapt to its circumstances such as customers' needs and the surrounding economic situations. To cope with this, a self organized IoT aware system is proposed. Here, awareness is achieved by monitoring analyzing the data of user's behavior such as gazing, listening, smelling etc. The focus here is the analysis of such as users' eye gaze, listening /smelling activity etc. The aim is to derive insights about products the user is interested in or not and to adapt the system accordingly. This is achieved by presenting product information including sales associates' presence, their voice, and product's smell or even other products with similar attributes, by hiding products with less interesting attributes and by building a user's interest model through integrating all the positive preferences.
IoT aware online shopping system enhanced with gaze analysis
Venue: 2016 World Automation Congress (WAC)

In online business, it is important to construct sale web pages offering attractive services for popular products in order to improve page access as well as purchase rates. Moreover, online shop owners need to hold various types of (campaign) sales frequently throughout the year to keep customers coming back. Also, online shopping systems have to adapt to its circumstances such as customers' needs and the surrounding economic situations. To cope with these requirements, a self organized IoT (Internet of Things) aware systems is proposed for online shopping. In our approach, awareness is achieved by monitoring/analyzing the data of user's behavior, in particular the eye gaze. The particular focus here is the analysis of the users' eye gaze with the objective to derive insights about products the user is interested in or not and adapt the system accordingly by presenting other products with similar attributes, hiding products with less interesting attributes and building a user's interest model by integrating all the positive preferences.
Multi hypothesis Kalman Filter for indoor pedestrian navigation based on topological maps
Venue: 2016 IEEE/ION Position, Location and Navigation Symposium (PLANS)

Location Based Services (LBS) require the knowledge of a user's position for manifold purposes in indoor and outdoor environments. For those applications several methods can be used, such as a Global Navigation Satellite System (GNSS) or a wireless localization system. In this paper a topological map is used to implement a indoor localization system for smartphone users. Benefit of this kind of map is that the position is reduced to one dimension, which simplifies the localization process in a considerable way. The map consists of vertices, which could be important points such as crossings or a ending point of a path, and edges, which represent ways between the vertices. The localization process utilizes different sensors of the smartphone, such as the accelerometer, the pressure sensor, Bluetooth Low Energy (BLE) and the integrated rotation sensor. To combine all of these information an Extended Kalman Filter (EKF) is introduced. To overcome crucial sensor information and thus to increase the robustness of the localization a multi hypotheses approach is implemented. Here different possible user positions on the topological map are instantiated and weighted. The implemented Kalman Filter is evaluated in several experiments which are recorded in an office building.
Using Brief Cognitive Restructuring and Cognitive Defusion Techniques to Cope With Negative Thoughts
Venue: Behavior modification

Negative thoughts, experienced by 80% to 99% of the non clinical population, have been linked to the development of psychopathology. The current study aimed to compare a cognitive restructuring and cognitive defusion technique for coping with a personally relevant negative thought. Over a 5 day period, participants used either a restructuring, defusion, or control strategy to manage a negative thought. Pre and post intervention participants reported (a) believability of the thought, (b) discomfort associated with the thought, (c) negativity associated with the thought, and (d) willingness to experience the thought. Daily online questionnaires assessing the total frequency of negative thought intrusions and their level of willingness to experience the negative thought were also used. Also, 10 positive and negative self statements were rated on the same scales, and self report measures of mood and psychological flexibility were completed. Findings indicated that defusion lowered believability, increased comfort and willingness to have the target thought, and increased positive affect significantly more than the control and cognitive restructuring. Within groups, cognitive restructuring also made significant gains in target thought discomfort, negativity, and "willingness to have" in the same direction as defusion but the no instruction control did not. Negative thought frequency was reduced in the defusion group, maintained in the restructuring group, and increased in the no instruction control group. Similar trends emerged from the secondary outcome measures, that is, the effects of the strategies on the positive and negative self statements. The current findings support the efficacy of using defusion as a strategy for managing negative thoughts.
The efficacy of imagery rescripting compared to cognitive restructuring for social anxiety disorder.
Venue: Journal of anxiety disorders

Imagery rescripting (IR) aims to alter negative meanings associated with distressing autobiographical memories. The current study aimed to extend demonstrated benefits of IR for social anxiety disorder (SAD) including direct comparison of IR with cognitive restructuring (CR) to assess the relative impact of these interventions on symptoms and processes. SAD individuals (N=60) were randomly allocated to IR, CR or Control conditions, and completed two speech tasks (before and after) their assigned intervention. Participants completed measures of symptomatology and state affective/cognitive variables in relation to the intervention and speech tasks. Results support the benefits of IR for SAD, with both IR and CR yielding large and equivalent reductions in trait social anxiety. However, IR and CR may function via differing pathways. Outcomes suggest that IR may be most effective in the treatment of SAD when delivered across multiple sessions or preceded by CR to target verbal and imaginal self representations.
Topiramate Combined with Cognitive Restructuring for the Treatment of Gambling Disorder: A Two Center, Randomized, Double Blind Clinical Trial
Venue: Journal of Gambling Studies

Gambling disorder (GD) is a prevalent condition for which no pharmacological treatment has yet been approved, although there is evidence that topiramate can reduce impulsivity in GD and craving in various addictive behaviors. The goal of this study was to investigate the effectiveness of topiramate combined with cognitive restructuring for GD in a two center, randomized, double blind clinical trial. Participants were individuals seeking outpatient treatment for GD (n 30) treated with either topiramate or placebo combined with a brief cognitive intervention, over a 12 week period, the dose of topiramate being tapered up during the first 8 weeks. The main outcome measures were gambling craving, behavior, and cognitive distortions; impulsivity; depression and social adjustment. Topiramate proved superior to placebo in reducing gambling craving (P 0.017) time and money spent gambling (P 0.007 and P 0.047, respectively) cognitive distortions related to gambling (P 0.003) and social adjustment (P 0.040) We found no significant effects on impulsivity or depression. These findings are in contrast with data from a previous clinical trial with topiramate for GD. In the current study, we found that topiramate affects features specifically related to gambling addiction and had no significant effect on associated phenomena such as impulsiveness and depression. We believe that this response could be due to synergistic interaction between topiramate and the cognitive intervention.
Behavioral and emotional consequences of thought listing versus cognitive restructuring during discarding decisions in hoarding disorder.
Venue: Behaviour research and therapy

An essential criterion for hoarding disorder (HD) is difficulty discarding or parting with possessions, yet few studies have examined reactions to actual discarding behaviors. The present study examined whether individuals with HD differed from non hoarding community controls (CC) in discarding behavior and emotional reactions to discarding. A second purpose was to examine the course of experienced distress following discarding. A third purpose was to determine whether HD participants responded differently to a simple thought listing (TL) instruction or to a cognitive restructuring (CR) protocol. Participants were asked to decide whether to keep or discard (a) a personal possession and (b) a newly acquired object (magazine) HD participants anticipated more and longer distress and reported stronger attachment motives than community controls, but they did not differ significantly from community controls in actual discarding behavior. TL was somewhat more effective than CR in improving discarding behavior and reducing negative emotions and attachments to discarded objects among HD participants. Reductions in distress were observed for both HD TL and HD CR groups. Thought listing may have reduced avoidance of decision making about discarding or perhaps CR, but not TL, provoked therapeutic reactance. Discarding was not related to reductions in distress or hoarding related beliefs.
PlanHab: the combined and separate effects of 16 days of bed rest and normobaric hypoxic confinement on circulating lipids and indices of insulin sensitivity in healthy men.
Venue: Journal of applied physiology

PlanHab is a planetary habitat simulation study. The atmosphere within future space habitats is anticipated to have reduced Po2, but information is scarce as to how physiological systems may respond to combined exposure to moderate hypoxia and reduced gravity. This study investigated, using a randomized crossover design, how insulin sensitivity, glucose tolerance, and circulating lipids were affected by 16 days of horizontal bed rest in normobaric normoxia [NBR: FiO2 0.209; PiO2 133.1 (0.3) mmHg] horizontal bed rest in normobaric hypoxia [HBR: FiO2 0.141 (0.004) PiO2 90.0 (0.4) mmHg] and confinement in normobaric hypoxia combined with daily moderate intensity exercise (HAMB) A mixed meal tolerance test, with arterialized venous blood sampling, was performed in 11 healthy, nonobese men (25 45 yr) before (V1) and on the morning ofday 17of each intervention (V2) Postprandial glucose and c peptide response were increased at V2 of both bed rest interventions (P< 0.05 in each case) with c peptide:insulin ratio higher at V2 in HAMB and HBR, both in the fed and fasted state (P< 0.005 in each case) Fasting total cholesterol was reduced at V2 in HAMB 0.47 (0.36) mmol/l;P< 0.005] and HBR 0.55 (0.41) mmol/l;P< 0.005] Fasting HDL was lower at V2 in all interventions, with the reduction observed in HBR 0.30 (0.21) mmol/l] greater than that measured in HAMB 0.13 (0.14) mmol/l;P< 0.005] and NBR 0.17 (0.15) mmol/l;P< 0.05] Hypoxia did not alter the adverse effects of bed rest on insulin sensitivity and glucose tolerance but appeared to increase insulin clearance. The negative effect of bed rest on HDL was compounded in hypoxia, which may have implications for long term health of those living in future space habitats.
Electronic, magnetic and thermal properties of Co2CrxFe1 xX (X=Al, Si) Heusler alloys: First principles calculations

Density functional theory (DFT) based on the full potential linearized augmented plane wave (FP LAPW) method is used to investigate the structural, electronic, magnetic and thermal properties of Co2CrxFe1 xX (X=Al, Si) full Heusler alloys, with L21 structure. The structural properties and spin magnetic moments are investigated by the generalized gradient approximations (GGA) minimizing the total energy. For band structure calculations, GGA, the Engel Vosko generalized gradient approximation (EVGGA) and modified Becke Johnson (mBJ) schemes are used. Results of density of states (DOS) and band structures show that these alloys are half metallic ferromagnets (HMFS) A regular solution model has been used to investigate the thermodynamic stability of the compounds Co2CrxFe1 xX that indicates a phase miscibility gap. The thermal effects using the quasi harmonic Debye model are investigated within the lattice vibrations. The temperature and pressure effects on the heat capacities, Debye temperatures and entropy are determined from the non equilibrium Gibbs functions.