nils-herrmann/clean_scirepeval huggingface dataset:
Standing in Your Peer's Shoes Hurts Your Feats: The Self Others Discrepancy in Risk Attitude and Impulsivity
Venue: Front. Psychol.

It is often a good strategy to "stand in the other person's shoes" to see a situation from a different perspective. People frequently attempt to infer what someone else would recommend when no advisor is available to help with a decision. Such situations commonly concern intertemporal or risky choices, and the usual assumption is that lay people make such decisions differently than experts do. The aim of our study was to determine what intertemporal and risky decisions people make when they take their own perspective, the perspective of a peer, and the perspectives of an expert or an entrepreneur. In a series of three experiments using a between subject design, we found that taking the peer's perspective made participants behave more impulsively and more risk aversely in relation to the participants' own perspectives and in relation to their perceptions of experts and entrepreneurs perspectives. Taking an expert's or an entrepreneur's perspective did not change participants' own intertemporal and risky decisions. We explain the findings using the risk as value and the lesser mind theories. Imagining the opponent's perspective in a negotiation as one is advised to do might inadvertently lead to problems because we always see her as more impulsive and more risk averse than she really is. This means that taking a perspective of an expert not a peer would be a good way to predict what decisions our opponents make.
Long Term Precipitation Analysis and Estimation of Precipitation Concentration Index Using Three Support Vector Machine Methods

The monthly precipitation data from 29 stations in Serbia during the period of 1946 2012 were considered. Precipitation trends were calculated using linear regression method. Three CLINO periods (1961 1990, 1971 2000, and 1981 2010) in three subregions were analysed. The CLINO 1981 2010 period had a significant increasing trend. Spatial pattern of the precipitation concentration index (PCI) was presented. For the purpose of PCI prediction, three Support Vector Machine (SVM) models, namely, SVM coupled with the discrete wavelet transform (SVM Wavelet) the firefly algorithm (SVM FFA) and using the radial basis function (SVM RBF) were developed and used. The estimation and prediction results of these models were compared with each other using three statistical indicators, that is, root mean square error, coefficient of determination, and coefficient of efficiency. The experimental results showed that an improvement in predictive accuracy and capability of generalization can be achieved by the SVM Wavelet approach. Moreover, the results indicated the proposed SVM Wavelet model can adequately predict the PCI.
Comparison of SEER Treatment Data With Medicare Claims
Venue: Medical care

The population based Surveillance, Epidemiology, and End Results (SEER) registries collect information on first course treatment, including surgery, chemotherapy, radiation therapy, and hormone therapy. However, the SEER program does not release data on chemotherapy or hormone therapy due to uncertainties regarding data completeness. Activities are ongoing to investigate the opportunity to supplement SEER treatment data with other data sources. Using the linked SEER Medicare data, we examined the validity of the SEER data to identify receipt of chemotherapy and radiation therapy among those aged 65 and older diagnosed from 2000 to 2006 with bladder, female breast, colorectal, lung, ovarian, pancreas, or prostate cancer and hormone therapy among men diagnosed with prostate cancer at age 65 or older. Treatment collected by SEER was compared with treatment as determined by Medicare claims, using Medicare claims as the gold standard. The &kgr; sensitivity, specificity, positive predictive values, and negative predictive values were calculated for the receipt of each treatment modality. The overall sensitivity of SEER data to identify chemotherapy, radiation, and hormone therapy receipt was moderate (68% 80% and 69% respectively) and varied by cancer site, stage, and patient characteristics. The overall positive predictive value was high >85% for all treatment types and cancer sites except chemotherapy for prostate cancer. SEER data should not generally be used for comparisons of treated and untreated individuals or to estimate the proportion of treated individuals in the population. Augmenting SEER data with other data sources will provide the most accurate treatment information.
Identifiability in Blind Deconvolution With Subspace or Sparsity Constraints
Venue: IEEE Transactions on Information Theory

Blind deconvolution (BD) the resolution of a signal and a filter given their convolution, arises in many applications. Without further constraints, BD is ill posed. In practice, subspace or sparsity constraints have been imposed to reduce the search space, and have shown some empirical success. However, the existing theoretical analysis on uniqueness in BD is rather limited. In an effort to address the still open question, we derive sufficient conditions under which two vectors can be uniquely identified from their circular convolution, subject to subspace or sparsity constraints. These sufficient conditions provide the first algebraic sample complexities for BD. We first derive a sufficient condition that applies to almost all bases or frames. For BD of vectors in Cn, with two subspace constraints of dimensions m1 and m2, the required sample complexity is n m1m2. Then, we impose a sub band structure on one basis, and derive a sufficient condition that involves a relaxed sample complexity n> m1+m2 1, which we show to be optimal. We present the extensions of these results to BD with sparsity constraints or mixed constraints, with the sparsity level replacing the subspace dimension. The cost for the unknown support in this case is an extra factor of 2 in the sample complexity.
A review of critical evaluation of natural ester vis a vis mineral oil insulating liquid for use in transformers: Part II
Venue: IEEE Transactions on Dielectrics and Electrical Insulation

In 130 years the power transformer has grown in many aspects; ratings, performance, technology, aesthetics and eco friendliness. Today, the transformer industry is witnessing the era of shifting from petroleum based mineral oils that are depleting, environmentally unfavorable, and proven dangerous to natural esters (vegetable oil based) that are renewable, environmentally friendly, and non hazardous. The market and regulatory pressures to reduce liability risk exposure of mineral oil filled distribution and power transformers are increasing. In addition, there are demands to improve equipment efficiency and adopt more "earth friendly" options in our power systems. In the last two decades there has been a resurgence of usage of natural ester insulating liquids for their "GREEN" and Safety credentials. These renewable resources have good dielectric properties and are compatible for use in power transformers. This paper evaluates and relates the new natural ester oil with existing mineral oil technology in terms of environmental concern, fire safety, physio chemical properties, thermal performance, and dielectric performance. It also covers key modifications in design, manufacturing and operation to help assure excellent functionality and long life. In brief, this paper provides transformer designers and users about the advantages and challenges of "green insulating liquid" Due to the voluminous properties that are compared and discussed, this paper is presented in two parts: Part I discusses the key properties and standards for the two liquids. Part II emphasizes additional key properties and material compatibility related to electrical design. Based on evidence discussed in both parts, it is concluded that natural esters are acceptable for both new transformers and for retro filling existing units.
A review on critical evaluation of natural ester vis a vis mineral oil insulating liquid for use in transformers: Part 1
Venue: IEEE Transactions on Dielectrics and Electrical Insulation

In a long 130 years of its journey in service to mankind, the power transformer has grown in many aspects; ratings, performance, technology, aesthetics and eco friendliness. Today, the transformer industry is witnessing the era of shifting from petroleum based mineral oils that are depleting, environmentally unfavorable, and proven dangerous to natural esters (vegetable oil based) that are renewable, environmentally friendly, and non hazardous. The market and regulatory pressures to reduce liability risk exposure of mineral oil filled distribution and power transformers are increasing. In addition, there are demands to improve equipment efficiency and adopt more "earth friendly" options in our power systems. In the last two decades there has been a resurgence of usage of natural ester insulating liquids for their "GREEN" and Safety credentials. These renewable resources have good dielectric properties and are compatible for use in power transformers. This paper evaluates and relates the new natural ester oil with existing mineral oil technology in terms of environmental concern, fire safety, physio chemical properties, thermal performance, and dielectric performance. It also covers key modifications in design, manufacturing and operation to help assure excellent functionality and long life. In brief, this paper provides transformer designers and users about the advantages and challenges of "Green Insulating Liquid" Due to the voluminous properties that are compared and discussed, this paper is presented in two parts: Part 1 discusses on key properties and standards for the two liquids. Part 2 emphasizes on additional key properties and material compatibility related to electrical design. Based on evidence discussed in both parts, it is concluded that natural esters are acceptable for both new transformers and for retro filling existing units.
THE EFFECTS OF HORTICULTURAL THERAPY ON THE PSYCHOLOGICAL WELL BEING AND ASSOCIATED BIOMARKERS OF ELDERLY IN SINGAPORE
Venue: Alzheimer's Dementia

improved balance, there were striking increases in community structure of somatomotor brain regions in PWD (Fig.2) Self reported QOL improved in 3 of the 5 PWD in the intervention group and declined in 4 of 5 PWD in the control group, although this did not reach statistical significance (b1/41.39, 95% CI 2.3 to 5.0] Positive results were noted for CG in balance, PHLMS awareness SF 36 general health, SF 36 emotional well being, and mood, although none of these reached statistical significant. Improved consistency was noted in somatomotor brain networks of CG. Neuropsychiatric symptoms and increased fall risk often accompany cognitive decline in dementia. Results from this pilot study suggest that an improvisational movement class that combines an engaging social environment with movement can improve balance, alter brain networks, and affect quality of life in PWD and their caregivers.
Highly Sensitive Wireless Sensor Node Using Surface Acoustic Wave Devices for Structural Health Monitoring

A wireless node of strain sensor was developed for structural health monitoring. Surface acoustic wave oscillators were used as sensor heads of the system, and can linearly detect the strain of 10 5 to 10 6 order. In the developed sensor node, a mixer chip and communicator were integrated on the board for temperature compensation and construction of sensor mesh network. We practically applied the developed sensor nodes to measurement of the static deformation in the metal plate, and successfully detected the deformation distribution. In this experiment, power consumption of each node was 190 uW in sleep mode and 50 mW in data transmission mode.
Word Embeddings, Analogies, and Machine Learning: Beyond king man woman queen
Venue: COLING

Solving word analogies became one of the most popular benchmarks for word embeddings on the assumption that linear relations between word pairs (such as king:man woman:queen) are indicative of the quality of the embedding. We question this assumption by showing that the information not detected by linear offset may still be recoverable by a more sophisticated search method, and thus is actually encoded in the embedding. The general problem with linear offset is its sensitivity to the idiosyncrasies of individual words. We show that simple averaging over multiple word pairs improves over the state of the art. A further improvement in accuracy (up to 30% for some embeddings and relations) is achieved by combining cosine similarity with an estimation of the extent to which a candidate answer belongs to the correct word class. In addition to this practical contribution, this work highlights the problem of the interaction between word embeddings and analogy retrieval algorithms, and its implications for the evaluation of word embeddings and the use of analogies in extrinsic tasks.
Stakeholders' expectations of mobile payment in retail: lessons from Sweden

The purpose of this paper is to explore the reasons behind the slow adoption of mobile payment services. The expectations of the main groups of stakeholders the mobile service providers, the retailers, and the consumers of the service in the retail industry in Sweden are examined.  The authors use a qualitative case study of stakeholders' expectations. The conceptual research framework is based on the theory of diffusion of innovations, the technology adoption model, and network externalities. The proposed framework was tested and validated by empirical findings.  One of the key findings of the research highlights that acceptance of a mobile payment service depends on the ability of mobile payment providers to build networks of both retailers and consumers simultaneously. The service will attract these stakeholders if it meets their expectations in the best possible way. Another finding is that mobile payment services do not meet expectations on an enha.
Load sharing behavior analysis method of wind turbine gearbox in consideration of multiple errors

Conducting a further analysis on loading sharing among compound planetary gear system in wind turbine gearbox, and making a meshing error analysis on the eccentricity error, gear thickness error, base pitch error, assembly error, and bearing error of wind turbine gearbox respectively. In view of the floating meshing error resulting from meshing clearance variation caused by the simultaneous floating of all gears, this paper establishes a refined mathematical model of two stage power split loading sharing coefficient calculation in consideration of multiple errors. Also obtains the regular curves of the load sharing coefficient and floating orbits of center gears, and conducts a load sharing coefficient test experiment of compound planetary gear system to verify the research results, which can provide scientific theory evidence for proper tolerance distribution and control in design and process.
Statistical fault diagnosis of wind turbine drivetrain applied to a 5MW floating wind turbine

Deployment of large scale wind turbine parks, in particular offshore, requires well organized operation and maintenance strategies to make it as competitive as the classical electric power stations. It is important to ensure systems are safe, profitable, and cost effective. In this regards, the ability to detect, isolate, estimate, and prognose faults plays an important role. One of the critical wind turbine components is the gearbox. Failures in the gearbox are costly both due to the cost of the gearbox itself and also due to high repair downtime. In order to detect faults as fast as possible to prevent them to develop into failure, statistical change detection is used in this paper. The Cumulative Sum Method (CUSUM) is employed to detect possible defects in the downwind main bearing. A high fidelity gearbox model on a 5 MW spar type wind turbine is used to generate data for fault free and faulty conditions of the bearing at the rated wind speed and the associated wave condition. Acceleration measurements are utilized to find residuals used to indirectly detect damages in the bearing. Residuals are found to be nonGaussian, following a t distribution with multivariable characteristic parameters. The results in this paper show how the diagnostic scheme can detect change with desired false alarm and detection probabilities.
Design and Implementation of Standby Power Saving Smart Socket with Wireless Sensor Network

Most Electrical Appliance in home still use electricity while turned off. Turned off electric appliance generally still require standby power when they are plugged in. In this paper we proposed a way to reduce standby power of electric home appliance and ZigBee based smart meter for smart grid application. The proposed socket supplies the appliances with power when the user turns them on. Our socket shuts the electric power off and reduces the standby power to zero when the user turns them off. The proposed design uses a microcontroller unit (MCU) receives signals from a Core Balanced Current Transformer (CBCT) and from a Pyroelectric Infrared (PIR) sensor which detects the user approaching the socket and provides MCU to control the relay On/Off when used as an appliance switch for shutting off the standby power. The components used in the proposed design are low cost and consume only 0.5 W. The MCU monitoring program provides both automatic detection of the user by the PIR sensor and detection of power consumption. The MCU measure the instantaneous current values and send it to data center computer through ZigBee module which acts as a smart meter for smart grid application.
The Interaction between Arbuscular Mycorrhizal Fungi and Endophytic Bacteria Enhances Plant Growth of Acacia gerrardii under Salt Stress
Venue: Front. Microbiol.

Microbes living symbiotically in plant tissues mutually cooperate with each other by providing nutrients for proliferation of the partner organism and have a beneficial effect on plant growth. However, few studies thus far have examined the interactive effect of endophytic bacteria and arbuscular mycorrhizal fungi (AMF) in hostile conditions and their potential to improve plant stress tolerance. In this study, we investigated how the synergistic interactions of endophytic bacteria and AMF affect plant growth, nodulation, nutrient acquisition and stress tolerance of Acacia gerrardii under salt stress. Plant growth varied between the treatments with both single inoculants and was higher in plants inoculated with the endophytic B. subtilis strain than with AMF. Co inoculated A. gerrardii had a significantly greater shoot and root dry weight, nodule number, and leghemoglobin content than those inoculated with AMF or B. subtilis alone under salt stress. The endophytic B. subtilis could alleviate the adverse effect of salt on AMF colonization. The differences in nitrate and nitrite reductase and nitrogenase activities between uninoculated plants and those inoculated with AMF and B. subtilis together under stress were significant. Both inoculation treatments, either B. subtilis alone or combined with AMF, enhanced the N, P, K, Mg, and Ca contents and phosphatase activities in salt stressed A. gerrardii tissues and reduced Na and Cl concentration, thereby protecting salt stressed plants from ionic and osmotic stress induced changes. In conclusion, our results indicate that endophytic bacteria and AMF contribute to a tripartite mutualistic symbiosis in A. gerrardii and are coordinately involved in the plant adaptation to salt stress tolerance.
Soft robotics: Technologies and systems pushing the boundaries of robot abilities
Venue: Science Robotics

Soft materials and deformable structures have given robots the ability to stretch, squash, climb, and morph, with potential for biodegradability and self healing. The proliferation of soft robotics research worldwide has brought substantial achievements in terms of principles, models, technologies, techniques, and prototypes of soft robots. Such achievements are reviewed here in terms of the abilities that they provide robots that were not possible before. An analysis of the evolution of this field shows how, after a few pioneering works in the years 2009 to 2012, breakthrough results were obtained by taking seminal technological and scientific challenges related to soft robotics from actuation and sensing to modeling and control. Further progress in soft robotics research has produced achievements that are important in terms of robot abilities that is, from the viewpoint of what robots can do today thanks to the soft robotics approach. Abilities such as squeezing, stretching, climbing, growing, and morphing would not be possible with an approach based only on rigid links. The challenge ahead for soft robotics is to further develop the abilities for robots to grow, evolve, self heal, develop, and biodegrade, which are the ways that robots can adapt their morphology to the environment.
Decentralized Cooperative Lane Changing Decision Making for Connected Autonomous Vehicles*
Venue: IEEE Access

In this paper, we proposed a decentralized cooperative lane changing decision making framework for connected autonomous vehicles, which is composed of three modules, i.e. state prediction, candidate decision generation, and coordination. In other words, each connected autonomous vehicle makes cooperative lane changing decision independently. In the state prediction module, we employed existing cooperative car following models to predict the vehicles' future state. In the candidate decision generation module, we proposed incentive based model to generate a candidate decision. In the candidate decision coordination module, we proposed an algorithm to avoid candidate lane changing decision that may lead to a vehicle collision or traffic deterioration to be final decision. Moreover, the effects of decentralized cooperative lane changing decision making framework on traffic stability, efficiency, homogeneity, and safety are investigated in a numerical simulation experiment. Some stability, efficiency, homogeneity, and safety indicators are evaluated and show the high potential of our proposed framework in traffic dynamics.
Lane Change and Merge Maneuvers for Connected and Automated Vehicles: A Survey
Venue: IEEE Transactions on Intelligent Vehicles

Intelligence in vehicles has developed through the years as self driving expectations and capabilities have increased. To date, the majority of the literature has focused on longitudinal control topics (e.g. Adaptive Cruise Control (ACC) Cooperative ACC (CACC) etc. To a lesser extent, there have been a variety of research articles specifically dealing with lateral control, e.g. maneuvers such as lane changes and merging. This paper provides a survey of this particular area of vehicle automation. The key topics addressed are control systems, positioning systems, communication systems, simulation modeling, field tests, surroundings vehicles, and human factors. Overall, there has been some successful research and field testing in lane change and merge maneuvers; however, there is a strong need for standardization and even more research to enable comprehensive field testing of these lateral maneuvers, so that commercial implementation of automated vehicles can be realized.