nils-herrmann/clean_scirepeval huggingface dataset:
Simulation using MATLAB/Simulink on rotor winding inter turn short circuit fault in DFIG
Venue: 2016 IEEE International Conference on Dielectrics (ICD)

A doubly fed induction generator (DFIG) has been frequently used in wind turbines, due to its simple working principle, reliable and fast process of electricity generation. DFIG has been affected negatively by inter turn short circuit fault of rotor windings, therefore it's of core importance to detect these faults at their initial stages to avoid catastrophic failure of the machine. For this purpose, a new method based on simple electrical parameters is proposed in this paper, to detect inter turn short circuit fault in rotor winding. The inter turn short circuit is modeled on rotor winding of DFIG by adding a resistor parallel to one phase (Phase a) of the rotor. The desired model is implemented in the MATLAB/Simulink. The simulation work in this paper is presented for normal operation and inter turn short circuit at different levels of fault. As the model is established in simple abc coordinate, so it doesn't need any transformation techniques. RMS values of rotor current, positive and negative sequence of current, and phase differences of the rotor current are used to analyze the fault. The results obtained through simulation depict that the analysis performed is quite appropriate as desired. Furthermore, the proposed technique applied is easy and reliable, due to its simple electrical input in wind turbine.
Influence of Conflict Management on Improved Personnel Performance in the Bank of Industry and Mining

This research sought to evaluate the influence of conflict management on improved performance of personnel at the Bank of Industry and Mining. Statistical population under study consisted of employees of the Bank of Industry and Mining of Tehran where 100 individuals among them were selected as statistical sample for participation in the study. This was a field study were by use of the survey method, questionnaire was used for data collection. Ultimately, for data analysis Pearson's correlation coefficient and regression analysis were used with the help of SPSS software. Results obtained showed that all three variables of identification of the kind of conflict, management of severity of conflict and management of duration of conflict are effective on performance of employees at the Bank of Industry and Mining, Tehran.
Analysis of Spatial Variation of Soil Salinization Using a Hydrochemical and Stable Isotopic Method in a Semiarid Irrigated Basin, Hetao Plain, Inner Mongolia, North China
Venue: Environmental Processes

This paper focuses on using data of total dissolved solids and stable isotopes of groundwater to confirm the spatial variation of soil salinization on the Hetao Plain of Inner Mongolia. The results show that soil salt contents, total dissolved solids and stable isotopes in the northwestern Hetao Plain have increased values. This was caused by water sources with large values of total dissolved solids and d18O, the rise of the groundwater table, and strong evaporation. However, there was another pattern in the eastern study area. Groundwater samples showed low d18O values and large total dissolved solids values, but salt contents had a checkered high and low distribution. Irrigation from Yellow River water, which is flushing farmland, has increased the salinity of groundwater, but d18O values were relatively small and clearly have reduced soil salt contents in the mid eastern area. Near Lake Wuliangsu, substantial farmland drainage water with many nutrients have entered the lake through waste canals, and groundwater with increased total dissolved solids values have increased the soil salt content. Some sites showed lower total dissolved solids and d18O values in the central area, revealing that channeled stream water from the Yellow River is the reason of low soil salt contents. A combined method of hydrochemistry and stable isotopes may be advantageous for analyzing soil salinization in a semiarid irrigated basin and for oases of semiarid regions in the world.
Kernelized Information Theoretic Metric Learning for Cancer Diagnosis Using High Dimensional Molecular Profiling Data
Venue: ACM Trans. Knowl. Discov. Data

With the advancement of genome wide monitoring technologies, molecular expression data have become widely used for diagnosing cancer through tumor or blood samples. When mining molecular signature data, the process of comparing samples through an adaptive distance function is fundamental but difficult, as such datasets are normally heterogeneous and high dimensional. In this article, we present kernelized information theoretic metric learning (KITML) algorithms that optimize a distance function to tackle the cancer diagnosis problem and scale to high dimensionality. By learning a nonlinear transformation in the input space implicitly through kernelization, KITML permits efficient optimization, low storage, and improved learning of distance metric. We propose two novel applications of KITML for diagnosing cancer using high dimensional molecular profiling data: (1) for sample level cancer diagnosis, the learned metric is used to improve the performance of k nearest neighbor classification; and (2) for estimating the severity level or stage of a group of samples, we propose a novel set based ranking approach to extend KITML. For the sample level cancer classification task, we have evaluated on 14 cancer gene microarray datasets and compared with eight other state of the art approaches. The results show that our approach achieves the best overall performance for the task of molecular expression driven cancer sample diagnosis. For the group level cancer stage estimation, we test the proposed set KITML approach using three multi stage cancer microarray datasets, and correctly estimated the stages of sample groups for all three studies.
Distributed Information Theoretic Metric Learning in Apache Spark
Venue: 2016 International Joint Conference on Neural Networks (IJCNN)

Distance metric learning (DML) is an effective similarity learning tool to learn a distance function from examples to enhance the model performance in applications of classification, regression, and ranking, etc. Most DML algorithms need to learn a Mahalanobis matrix, a positive semidefinite matrix that scales quadratically with the number of dimensions of input data. This brings huge computational cost in the learning procedure, and makes all proposed algorithms infeasible for extremely high dimensional data even with the low rank approximation. Differently, in this paper, we take advantage of the power of parallel computation and propose a novel distributed distance metric learning algorithm based on a state of the art DML algorithm, Information Theoretic Metric Learning (ITML).More specifically, we utilize the property that each positive semidefinite matrix can be decomposed into a combination of rank one and trace one matrices and convert the original sequential training procedure into a parallel one. In most cases, the communication demands of the proposed method are also reduced from O(d2) to O(cd) where d is the number of dimensions of the data and c is the number of constraints in DML and can be smaller than d by appropriate selection. Moreover importantly, we present a rigorous theoretical analysis to upper bound the Bregman divergence between the sequential algorithm and the parallel algorithm, which guarantees the correctness and performance of the proposed algorithm. Our experiments on datasets with O(105) features demonstrate the competitive scalability and the performance compared with the original ITML algorithm.
MultiCol SLAM A Modular Real Time Multi Camera SLAM System
Venue: ArXiv

The basis for most vision based applications like robotics, self driving cars and potentially augmented and virtual reality is a robust, continuous estimation of the position and orientation of a camera system w.r.t the observed environment (scene) In recent years many vision based systems that perform simultaneous localization and mapping (SLAM) have been presented and released as open source. In this paper, we extend and improve upon a state of the art SLAM to make it applicable to arbitrary, rigidly coupled multi camera systems (MCS) using the MultiCol model. In addition, we include a performance evaluation on accurate ground truth and compare the robustness of the proposed method to a single camera version of the SLAM system. An open source implementation of the proposed multi fisheye camera SLAM system can be found on line this https URL
Worklife and Wellness in Academic General Internal Medicine: Results from a National Survey
Venue: Journal of General Internal Medicine

ABSTRACTBACKGROUNDGeneral internal medicine (GIM) careers are increasingly viewed as challenging and unsustainable.OBJECTIVEWe aimed to assess academic GIM worklife and determine remediable predictors of stress and burnout.DESIGNWe conducted an email survey.PARTICIPANTSPhysicians, nurse practitioners, and physician assistants in 15 GIM divisions participated.MAIN MEASURESA ten item survey queried stress, burnout, and work conditions such as electronic medical record (EMR) challenges. An open ended question assessed stressors and solutions. Results were categorized into burnout, high stress, high control, chaos, good teamwork, high values alignment, documentation time pressure, and excessive home EMR use. Frequencies were determined for national data, Veterans Affairs (VA) versus civilian populations, and hospitalist versus ambulatory roles. A General Linear Mixed Model (GLMM) evaluated associations with burnout. A formal content analysis was performed for open ended question responses.KEY RESULTSOf 1235 clinicians sampled, 579 responded (47 High stress was present in 67 with 38 burned out (burnout range 10 56 by division) Half of respondents had low work control, 60 reported high documentation time pressure, half described too much home EMR time, and most reported very busy or chaotic workplaces. Two thirds felt aligned with departmental leaders' values, and three quarters were satisfied with teamwork. Burnout was associated with high stress, low work control, and low values alignment with leaders (all p 0.001) The 45 VA faculty had less burnout than civilian counterparts (17 vs. 40 p 0.05) Hospitalists described better teamwork than ambulatory clinicians and fewer hospitalists noted documentation time pressure (both p 0.001) Key themes from the qualitative analysis were short visits, insufficient support staff, a Relative Value Unit mentality, documentation time pressure, and undervaluing education.CONCLUSIONSWhile GIM divisions overall demonstrate high stress and burnout, division rates vary widely. Sustainability efforts within GIM could focus on visit length, staff support, schedule control, clinic chaos, and EMR stress.
Providing end of life care in general practice: findings of a national GP questionnaire survey.
Venue: The British journal of general practice the journal of the Royal College of General Practitioners

With increasing numbers of people living with complex life limiting multimorbidity in the community, consideration must be given to improving the organisation and delivery of high quality palliative and end of life care (EOLC)  To provide insight into the experience of GPs providing EOLC in the community, particularly the facilitators and barriers to good quality care.  A web based national UK questionnaire survey circulated via the Royal College of General Practitioners, NHS, Marie Curie, and Macmillan networks to GPs.  Responses were analysed using descriptive statistics and an inductive thematic analysis.  Responses were received from 516 GPs, who were widely distributed in terms of practice location. Of these, 97% felt that general practice plays a key role in the delivery of care to people approaching the end of life and their families. Four interdependent themes emerged from the data: continuity of care which can be difficult to achieve because of resource concerns including time, staff numbers, increasing primary care workload, and lack of funding; patient and family factors with challenges including early identification of palliative care needs and recognition of the end of life, opportunity for care planning discussions, and provision of support for families; medical management including effective symptom control and access to specialist palliative care services; and expertise and training the need for training and professional development was recognised to enhance knowledge, skills, and attitudes towards EOLC.  The findings reveal enduring priorities for policy, commissioning, practice development, and research in future primary palliative care.
DELAY OF GERMINATION1 (DOG1) regulates both seed dormancy and flowering time through microRNA pathways
Venue: Proceedings of the National Academy of Sciences

Annual plants adapt to their environments by matching their life cycles, particularly seed germination and flowering, to the appropriate seasons. Although genetic evidence has suggested connections among genes regulating seed dormancy and flowering, specific mechanisms for such coordination are unknown. We report that a gene [DELAY OF GERMINATION1 (DOG1) involved in determining the depth of seed dormancy, and therefore the seasonal timing of germination, also influences the timing of flowering in Arabidopsis and lettuce. We further show that this gene acts through influencing the production of microRNAs that govern the progression of developmental phase transitions through the plant life cycle, providing a molecular genetic mechanism for the coordinate adaptation of seed dormancy and flowering phenotypes to environmental conditions. Seed germination and flowering, two critical developmental transitions in plant life cycles, are coordinately regulated by genetic and environmental factors to match plant establishment and reproduction to seasonal cues. The DELAY OF GERMINATION1 (DOG1) gene is involved in regulating seed dormancy in response to temperature and has also been associated genetically with pleiotropic flowering phenotypes across diverse Arabidopsis thaliana accessions and locations. Here we show that DOG1 can regulate seed dormancy and flowering times in lettuce (Lactuca sativa, Ls) and Arabidopsis through an influence on levels of microRNAs (miRNAs) miR156 and miR172. In lettuce, suppression of LsDOG1 expression enabled seed germination at high temperature and promoted early flowering in association with reduced miR156 and increased miR172 levels. In Arabidopsis, higher miR156 levels resulting from overexpression of the MIR156 gene enhanced seed dormancy and delayed flowering. These phenotypic effects, as well as conversion of MIR156 transcripts to miR156, were compromised in DOG1 loss of function mutant plants, especially in seeds. Overexpression of MIR172 reduced seed dormancy and promoted early flowering in Arabidopsis, and the effect on flowering required functional DOG1. Transcript levels of several genes associated with miRNA processing were consistently lower in dry seeds of Arabidopsis and lettuce when DOG1 was mutated or its expression was reduced; in contrast, transcript levels of these genes were elevated in a DOG1 gain of function mutant. Our results reveal a previously unknown linkage between two critical developmental phase transitions in the plant life cycle through a DOG1 miR156 miR172 interaction.
Molecular Mechanisms of the Anti Obesity and Anti Diabetic Properties of Flavonoids
Venue: International journal of molecular sciences

Obesity and diabetes are the most prevailing health concerns worldwide and their incidence is increasing at a high rate, resulting in enormous social costs. Obesity is a complex disease commonly accompanied by insulin resistance and increases in oxidative stress and inflammatory marker expression, leading to augmented fat mass in the body. Diabetes mellitus (DM) is a metabolic disorder characterized by the destruction of pancreatic b cells or diminished insulin secretion and action insulin. Obesity causes the development of metabolic disorders such as DM, hypertension, cardiovascular diseases, and inflammation based pathologies. Flavonoids are the secondary metabolites of plants and have 15 carbon skeleton structures containing two phenyl rings and a heterocyclic ring. More than 5000 naturally occurring flavonoids have been reported from various plants and have been found to possess many beneficial effects with advantages over chemical treatments. A number of studies have demonstrated the potential health benefits of natural flavonoids in treating obesity and DM, and show increased bioavailability and action on multiple molecular targets. This review summarizes the current progress in our understanding of the anti obesity and anti diabetic potential of natural flavonoids and their molecular mechanisms for preventing and/or treating obesity and diabetes.
In Vitro Antioxidant versus Metal Ion Chelating Properties of Flavonoids: A Structure Activity Investigation
Venue: PloS one

Natural flavonoids such as quercetin, )catechin and rutin as well as four methoxylated derivatives of quercetin used as models were investigated to elucidate their impact on the oxidant and antioxidant status of human red blood cells (RBCs) The impact of these compounds against metal toxicity was studied as well as their antiradical activities with DPPH assay. Antihemolytic experiments were conducted on quercetin, )catechin and rutin with excess of Fe, Cu and Zn (400 mM) and the oxidant (malondialdehyde, carbonyl proteins) and antioxidant (reduced glutathione, catalase activity) markers were evaluated. The results showed that Fe and Zn have the highest prooxidant effect (37 and 33% of hemolysis, respectively) Quercetin, rutin and )catechin exhibited strong antioxidant properties toward Fe, but this effect was decreased with respect to Zn ions. However, the Cu showed a weak antioxidant effect at the highest flavonoid concentration (200 mM) while a prooxidant effect was observed at the lowest flavonoid concentration (100 mM) These results are in agreement with the physico chemical and antiradical data which demonstrated that binding of the metal ions (for FeNTA: )Catechin, KLFeNTA 1.6(1) x 106 M 1 Rutin, KLFeNTA 2.0(9) x 105 M 1 Quercetin, KLFeNTA 1.0(7) x 105 M 1 Q35OH, KLFeNTA 6.3(8.7) x 104 M 1 Quercetin3'4'OH and Quercetin 3OH, KLFeNTA 2 x 104 M 1) reflects the (anti)oxidant status of the RBCs. This study reveals that flavonoids have both prooxidant and antioxidant activity depending on the nature and concentration of the flavonoids and metal ions.
Field aware Factorization Machines for CTR Prediction
Venue: RecSys

Click through rate (CTR) prediction plays an important role in computational advertising. Models based on degree 2 polynomial mappings and factorization machines (FMs) are widely used for this task. Recently, a variant of FMs, field aware factorization machines (FFMs) outperforms existing models in some world wide CTR prediction competitions. Based on our experiences in winning two of them, in this paper we establish FFMs as an effective method for classifying large sparse data including those from CTR prediction. First, we propose efficient implementations for training FFMs. Then we comprehensively analyze FFMs and compare this approach with competing models. Experiments show that FFMs are very useful for certain classification problems. Finally, we have released a package of FFMs for public use.
Influence of Experiences on Memories, Satisfaction and Behavioral Intentions: A Study of Creative Tourism

To date, few empirical studies have focused on the constituents of creative tourists' experience and its consequences. This study aims to bridge this research gap by examining the effect of creative tourists' experience on their memories, satisfaction, and behavioral intentions. Data were collected from 296 creative tourists, selected through purposive sampling, at selected resort hotels in the Malaysian states of Terengganu and Kedah. The results show that creative tourist experience is a second order factor with five dimensions, namely escape and recognition, peace of mind, unique involvement, interactivity, and learning. The results of structural equation modeling show that creative tourists' experience is a good predictor of their memories, satisfaction, and behavioral intentions. The proposed model and findings can greatly help researchers and practitioners understand the concept of creative tourist experience and its complex relationships with their memories, satisfaction, and behavioral intentions.
Creative experiences, memorability and revisit intention in creative tourism

The objective of this study was to identify hypothesised relationships among creative experiences, memorability, and revisit intentions in creative tourism. Face to face questionnaire survey was adopted and 399 valid questionnaires were collected in the pottery town of Yingge in Taiwan. The results show significantly positive relationships among creative experiences, memorability, and revisit intentions. Structural equation modelling analysis verified that memorability fully mediated the effect of creative experiences on revisit intentions. The study suggests that memorability may be a more appropriate predictor to revisit intentions, particularly in the case of creative activities.
An Enduring Dilemma on the Korean Peninsula: The North Korean Nuclear Conundrum and South Korea`s Strategic Choices

This paper sheds new light on the North Korean nuclear conundrum, which has long been the source of security dilemmas on the Korean Peninsula, and South Korea's strategic choices with regard to it. In doing this, this paper deals with four research questions: 1) How serious are North Korea's nuclear and missile capabilities? 2) What are the implications of international sanctions and countries' positions? 3) Can and will South Korea and the international community stop the North Korean nuclear program successfully? and 4) And if not, what should South Korea do? This paper indicates that in the wake of North Korea's fourth nuclear test and subsequent missile test, North Korea's nuclear Pandora's Box is almost about to open. It urges that if it indeed opens, it would completely change the strategic environment of the Korean Peninsula and Northeast Asia. This deep frustration and a sense of urgency have driven South Korea and the international community to impose stronger and tougher sanctions against North Korea than before. However, this paper argues that multiple factors..South Korea's limited ability; the escalation of the U.S. China global and regional rivalry; the strategic consideration of countries involved, especially China; and North Korea's tenacious survival strategy engage in strong pessimism, leaving the North Korean nuclear situation unresolved. Therefore, on the one hand, South Korea has to make every effort to denuclearize North Korea until the last minute, exhausting every possible option and means. However, on the other hand, it has to prepare for a worst case scenario. This paper points out that South Korea's exit strategy should be a "strategy of delicate deterrence" that is a comprehensive strategy of deterrence to combine military, political and diplomatic means.
Clutch lining frictional characteristics under thermal tribodynamic conditions

The frictional performance of the clutch mating surfaces varies transiently during clutch engagement. The friction characteristics depend on the clamp load, relative slip speed of the mating surfaces and the generated contact temperature. These operating conditions affect the characteristics and lead to clutch take up judder during engagement. To study this phenomenon as well as issues relating to clutch wear, it is essential to evaluate the friction lining characteristics. This paper replicates the clutch conditions through careful experimentation with a fully instrumented pin on disc tribometer. It is shown that the kinetic coefficient of friction for the clutch friction lining material in contact with the sinusoidal wavy and rough surface of pressure plate decreases with rising contact temperature and increasing slip speed.