nils-herrmann/clean_scirepeval huggingface dataset:
Measuring precise radial velocities and cross correlation function line profile variations using a Skew Normal density
Venue: Astronomy Astrophysics
Year: 2019

Stellar activity is one of the primary limitations to the detection of low mass exoplanets using the radial velocity (RV) technique. Stellar activity can be probed by measuring time dependent variations in the shape of the cross correlation function (CCF) It is therefore critical to measure with high precision these shape variations to decorrelate the signal of an exoplanet from spurious RV signals caused by stellar activity.  We propose to estimate the variations in shape of the CCF by fitting a Skew Normal (SN) density which, unlike the commonly employed Normal density, includes a Skewness parameter to capture the asymmetry of the CCF induced by stellar activity and the convective blueshift.  We compared the performances of the proposed method to the commonly employed Normal density using both simulations and real observations with different levels of activity and signal to noise ratios.  When considering real observations, the correlation between the RV and the asymmetry of the CCF and between the RV and the width of the CCF are stronger when using the parameters estimated with the SN density rather than those obtained with the commonly employed Normal density. In particular, the strongest correlations have been obtained when using the mean of the SN as an estimate for the RV. This suggests that the CCF parameters estimated using a SN density are more sensitive to stellar activity, which can be helpful when estimating stellar rotational periods and when characterizing stellar activity signals. Using the proposed SN approach, the uncertainties estimated on the RV defined as the median of the SN are on average 10% smaller than the uncertainties calculated on the mean of the Normal. The uncertainties estimated on the asymmetry parameter of the SN are on average 15% smaller than the uncertainties measured on the Bisector Inverse Slope Span (BIS SPAN) which is the commonly used parameter to evaluate the asymmetry of the CCF. We also propose a new model to account for stellar activity when fitting a planetary signal to RV data. Based on simple simulations, we were able to demonstrate that this new model improves the planetary detection limits by 12% compared to the model commonly used to account for stellar activity.  The SN density is a better model than the Normal density for characterizing the CCF since the correlations used to probe stellar activity are stronger and the uncertainties of the RV estimate and the asymmetry of the CCF are both smaller.
Automatic Adaptation of Object Detectors to New Domains Using Self Training
Venue: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2019

This work addresses the unsupervised adaptation of an existing object detector to a new target domain. We assume that a large number of unlabeled videos from this domain are readily available. We automatically obtain labels on the target data by using high confidence detections from the existing detector, augmented with hard (misclassified) examples acquired by exploiting temporal cues using a tracker. These automatically obtained labels are then used for re training the original model. A modified knowledge distillation loss is proposed, and we investigate several ways of assigning soft labels to the training examples from the target domain. Our approach is empirically evaluated on challenging face and pedestrian detection tasks: a face detector trained on WIDER Face, which consists of high quality images crawled from the web, is adapted to a large scale surveillance data set; a pedestrian detector trained on clear, daytime images from the BDD 100K driving data set is adapted to all other scenarios such as rainy, foggy, night time. Our results demonstrate the usefulness of incorporating hard examples obtained from tracking, the advantage of using soft labels via distillation loss versus hard labels, and show promising performance as a simple method for unsupervised domain adaptation of object detectors, with minimal dependence on hyper parameters.
Pengaruh Electronic Word of Mouth (E WOM) Terhadap Brand Image dan Purchase Intention Mobil Toyota di Surabaya
Year: 2015

Penelitian ini bertujuan untuk menguji Pengaruh Electronic Word of Mouth terhadap Brand Image dan Purchase Intention mobil Toyota di Surabaya. Penelitian ini menggunakan applied research yang menggunakan 3 variabel, yaitu Electronic word of mouth (E WOM) Brand Image dan Purchase Intention dimana sampel berupa responden yang pernah menggunakan produk Toyota dalam 6 bulan terakhir, pernah membaca review online, berdomisili di Surabaya dan berpendidikan minimal SMA atau sederajat. Responden dalam penelitian ini berjumlah 150 orang. Analisis dilakukan dengan menggunakan SPSS 18.0 for software dan dengan menggunakan model SEM (Structural Equation Modeling) melalui software AMOS 18.0 untuk pengujian measurement dan Structural. Hasil penelitian ini menunjukkan bahwa adanya pengaruh yang signifikan antara electronic word of mouth terhadap brand image dan purchase intention.
Text Graph Transformer for Document Classification
Venue: EMNLP
Year: 2020

Text classification is a fundamental problem in natural language processing. Recent studies applied graph neural network (GNN) techniques to capture global word co occurrence in a corpus. However, previous works are not scalable to large sized corpus and ignore the heterogeneity of the text graph. To address these problems, we introduce a novel Transformer based heterogeneous graph neural network, namely Text Graph Transformer (TG Transformer) Our model learns effective node representations by capturing structure and heterogeneity from the text graph. We propose a mini batch text graph sampling method that significantly reduces computing and memory costs to handle large sized corpus. Extensive experiments have been conducted on several benchmark datasets, and the results demonstrate that TG Transformer outperforms state of the art approaches on text classification task.
Implementation of an audit with feedback knowledge translation intervention to promote medication error reporting in health care: a protocol
Venue: Implementation Science
Year: 2015

BackgroundHealth professionals strive to deliver high quality care in an inherently complex and error prone environment. Underreporting of medical errors challenges attempts to understand causative factors and impedes efforts to implement preventive strategies. Audit with feedback is a knowledge translation strategy that has potential to modify health professionals' medical error reporting behaviour. However, evidence regarding which aspects of this complex, multi dimensional intervention work best is lacking. The aims of the Safe Medication Audit Reporting Translation (SMART) study are to:1. Implement and refine a reporting mechanism to feed audit data on medication errors back to nurses2. Test the feedback reporting mechanism to determine its utility and effect3. Identify characteristics of organisational context associated with error reporting in response to feedbackMethods/designA quasi experimental design, incorporating two pairs of matched wards at an acute care hospital, is used. Randomisation occurs at the ward level; one ward from each pair is randomised to receive the intervention. A key stakeholder reference group informs the design and delivery of the feedback intervention. Nurses on the intervention wards receive the feedback intervention (feedback of analysed audit data) on a quarterly basis for 12 months. Data for the feedback intervention come from medication documentation point prevalence audits and weekly reports on routinely collected medication error data. Weekly reports on these data are obtained for the control wards. A controlled interrupted time series analysis is used to evaluate the effect of the feedback intervention. Self report data are also collected from nurses on all four wards at baseline and at completion of the intervention to elicit their perceptions of the work context. Additionally, following each feedback cycle, nurses on the intervention wards are invited to complete a survey to evaluate the feedback and to establish their intentions to change their reporting behaviour. To assess sustainability of the intervention, at 6 months following completion of the intervention a point prevalence chart audit is undertaken and a report of routinely collected medication errors for the previous 6 months is obtained. This intervention will have wider application for delivery of feedback to promote behaviour change for other areas of preventable error and adverse events.
An ANP and MULTIMOORA Based SWOT Analysis for Strategy Formulation
Year: 2019

Since no organization can have unlimited resources, strategists should decide on a strategy that can provide the greatest benefits to the organization. Decisions on strategy formulation commit the organization to produce specific products, work in specific markets, and exploit certain resources and technologies for a relatively long time. Strategies dictate the long term competitive advantages of an organization. Either good or bad, strategic decisions have multifaceted results and long lasting consequences for organizations. So, organizations should adopt optimal strategies to move in the right direction and avoid irreparable losses. This planning calls for an optimal model of strategy formulation so that the strategists of organizations can formulate a strategy for their respected organizations readily and accurately. The present study presents a composite approach to organizational strategy formulation.
A high performance Balanced Power Amplifier and Its Integration into a Front end Module at PCS Band
Venue: 2007 IEEE Radio Frequency Integrated Circuits (RFIC) Symposium
Year: 2007

A novel load insensitive power amplifier (LIPA) with balanced structure is developed for 3G (HSDPA and HSUPA) handset application at PCS band from 1850 1910 MHz. No external regulated voltage and analog voltage supplies are required at high power level and it is compatible with DC to DC converters. Digital or analog control may be applied to further improve its PAE at low and middle power levels. This newly featured PA is integrated into a 4x7 mm2 front end module (FEM) with good performance, especially under load mismatch condition.
High energy density and power density thermal storage prototype with hydrated salt for hot water and space heating
Venue: Applied Energy
Year: 2019

Thermal energy storage is a key technology to promote renewable energy application and utilization of off peak electricity for space heating and hot water. Hydrated salt is one kind of promising phase change materials for thermal energy storage but it usually has the common drawbacks of phase separation, high supercooling degree and poor thermal conductivity as well as low power density due to slow charging discharging rates. Here, we develop a high energy density and high power density latent heat thermal energy storage prototype with heat capacity of 7.0 kWh by employing modified sodium acetate trihydrate with the aim of solving the phase separation and supercooling degree problems. The overall performance of latent heat thermal energy storage system with the prototype is evaluated for two different applications: hot water supply and space heating. The experimental results showed that the high power density thermal storage prototype has excellent thermal performance and its volumetric energy storage density is about 2.5 times higher than that of traditional water tank. The system energy efficiency is higher than 90% under different working conditions. For hot water supply mode, the average heating power is as high as 10.3 18.6 kW and hot water temperature can reach 50 degC at different inlet cold water temperatures varying between 7 and 25 degC. For spacing heating mode, the hot air temperature is higher than 40 degC and indoor room temperature can keep above 16 19.5 degC when the outdoor temperature ranges between 5 and 10 degC. The proposed prototype has the advantages of high energy density thermal storage, high power density energy supply, and fast charging discharging rates for hot water and space heating.
Research Review: What have we learned about adolescent substance use?
Venue: Journal of child psychology and psychiatry, and allied disciplines
Year: 2018

Adolescence is a critical biological, psychological, and social developmental stage involving heightened risk for substance use and associated adverse consequences. This review, synthesizing emerging findings on this complex topic, is intended to inform research and clinical care focused on adolescents.  Literature searches were conducted using PubMed, yielding a cross section of observational and interventional studies focused on adolescent substance use. Findings were organized and categorized to cover key areas of epidemiology, neurobiology, prevention, and treatment.  Adolescent substance related attitudes and use patterns have evolved over time, informed by adult and peer behaviors, public policy, media messaging, substance availability, and other variables. A number of risk and resiliency factors contribute to individual differences in substance use and related consequences. Advances in observational techniques have provided enhanced understanding of adolescent brain development and its implications for substance use. Prevention efforts have yielded mixed results, and while a number of adolescent targeted evidence based treatments for substance use disorders have been developed, effect sizes are generally modest, indicating the need for further research to enhance prevention and treatment outcomes.  Substance use in adolescence is heterogeneous, ranging from normative to pathological, and can lead to significant acute and long term morbidity and mortality. Understanding risk and resiliency factors, underlying neurobiology, and optimal developmentally sensitive interventions is critical in addressing substance associated problems in adolescence.
Analysis, Searching Sorting in Big data using Apache Hadoop
Year: 2016

Big Data is generally considered as a large collection of data sets (In PetaBytes) which are difficult to analyze, share, store, search, transference through traditional data processing applications. Apache Hadoop is a Java written application for Storing, Processing and Analyzing large datasets (i.e Big Data) with the help of in built Hadoop Distributed File System (HDFS) Yet Another Resource Negotiator (YARN) Map Reduce Algorithm type algorithms and additional software packages like Apache Pig, Apache Hive, Apache HBase, Apache Spark and others. The aim of this project is to minimize the response time for the Searching, Sorting and Analyzing of the Big Data using efficient algorithms and databases.
Penilaian User Experience Menggunakan Metode Technology Acceptance Model (TAM) Terhadap Aplikasi Augmented Reality Gamelan Jawa
Year: 2020

Gamelan merupakan salah satu budaya lokal Indonesia yang perlu dipelihara eksistensinya. Beberapa penelitian terkait pengenalan gamelan ke generasi muda telah banyak dilakukan, diantaranya menghasilkan aplikasi yang menggabungkan antara gamelan dengan teknologi terkini yaitu augmented reality. Penggunaan teknologi augmented reality untuk menampilkan dan memperkenalkan alat musik gamelan merupakan inovasi baru dan perlu diapresiasi. Namun perlu sebuah penilaian tersendiri untuk mengetahui apakah penggunaan teknologi tersebut berdampak positif terhadap penggunanya. Melalui penelitian ini, peneliti melakukan kajian lebih dalam dengan menggunakan metode Technology Acceptance Model (TAM) untuk mengetahui pengalaman pengguna dalam berinteraksi dengan aplikasi gamelan berbasis augmented reality. Terdapat lima aspek yang diuji yaitu aspek kemudahan penggunaan (Perceived Ease of Use) manfaat penggunaan (Perceived Usefulness) sikap pengguna (Atitude Toward Using) keinginan pengguna (Behavioral Intention of Use) kesadaran pengguna (Actual System Usage) Dari hasil uji validitas dan realibiltas yang dilakukan didapatkan hasil bahwa semua butir komponen dalam kuisoner yang dibagikan valid dan reliable. Sedangkan dari analisis data deskriptif yang dilakukan, didapatkan hasil bahwa persepsi pengguna terhadap lima aspek tersebut di atas sangat baik dengan nilai skor tertinggi 4.10 pada aspek kemudahan penggunaan dan sikap pengguna.
Origins of Diamond Surface Noise Probed by Correlating Single Spin Measurements with Surface Spectroscopy
Venue: Physical Review X
Year: 2019

The nitrogen vacancy (NV) center in diamond exhibits spin dependent fluorescence and long spin coherence times under ambient conditions, enabling applications in quantum information processing and sensing. NV centers near the surface can have strong interactions with external materials and spins, enabling new forms of nanoscale spectroscopy. However, NV spin coherence degrades within 100 nanometers of the surface, suggesting that diamond surfaces are plagued with ubiquitous defects. Prior work on characterizing near surface noise has primarily relied on using NV centers themselves as probes; while this has the advantage of exquisite sensitivity, it provides only indirect information about the origin of the noise. Here we demonstrate that surface spectroscopy methods and single spin measurements can be used as complementary diagnostics to understand sources of noise. We find that surface morphology is crucial for realizing reproducible chemical termination, and use these insights to achieve a highly ordered, oxygen terminated surface with suppressed noise. We observe NV centers within 10 nm of the surface with coherence times extended by an order of magnitude.
The Polar Environment Atmospheric Research Laboratory (PEARL) Sounding the Atmosphere at 80o North
Year: 2013

M ATMOSPHERIC MEASUREMENTS in the High Arctic is challenging because of the remoteness of the area, the difficult transportation, the inconsistent communications, and the extreme environmental conditions. In 2003, after the Environment Canada (EC) Arctic Stratospheric Ozone Observatory (AStrO) closed, the Canadian Network for the Detection of Atmospheric Change (CANDAC) a group of university and government scientists, identified a High Arctic observatory as a high priority need to improve research measurements over the Canadian portion of the Arctic. Significant effort was given to selecting a site and acquiring the required funding to populate it. This activity gained fresh urgency with the planning of the International Polar Year (IPY) in 2007 08. A High Arctic observatory would directly respond to the IPY intention not only to make intensive measurements throughout the IPY time frame, but also to "leave a legacy of observing sites, facilities and systems to support ongoing polar research and monitoring" (ICSU, 2004:10) After some consideration of alternative sites, CANDAC decided to concentrate activities at Eureka (80 N, 86 W,  The research site was designated the Polar Environment Atmospheric Research Laboratory (PEARL) and CANDAC began to seek funding for equipment and operations. PEARL, which formally began operations in 2005, supports research in three broad areas: air quality, ozone, and climate change. Subsequent experience has amply demonstrated the appropriateness of the site, and several advantages that were not apparent at the time of site selection affirm Eureka as a uniquely suitable location for atmospheric (and now other) measurements in the Canadian sector of the High Arctic.
MERCOSUL: surgimento, estrutura, direitos sociais, relacao com a Unasul, perspectivas de sua evolucao
Year: 2009

Aborda a origem do Mercosul e as razoes sociopoliticas de sua criacao. Apresenta sintese dos fatores historico sociais de seu surgimento, sua estrutura institucional e relacao com a Unasul, alem de expor a situacao dos direitos sociais e trabalhistas no contexto da integracao regional. Enfoca ainda as perspectivas de evolucao e consolidacao desse processo. PALAVRAS CHAVE Direito Internacional; Mercosul; Unasul; integracao regional; Alca; Tratado de Assuncao; consolidacao; direitos sociais; blocos economicos.
Are patients with hypertension and diabetes mellitus at increased risk for COVID 19 infection?
Venue: The Lancet Respiratory Medicine
Year: 2020

The most distinctive comorbidities of 32 non survivors from a group of 52 intensive care unit patients with novel coronavirus disease 2019 (COVID 19) in the study by Xiaobo Yang and colleagues were cerebro vascular diseases (22% and diabetes (22% Another study included 1099 patients with confirmed COVID 19, of whom 173 had severe disease with comorbidities of hypertension (23*7% diabetes mellitus (16*2% coronary heart diseases (5*8% and cerebrovascular disease (2*3% In a third study, of 140 patients who were admitted to hospital with COVID 19, 30% had hypertension and 12% had diabetes. Notably, the most frequent comorbidities reported in these three studies of patients with COVID 19 are often treated with angiotensin converting enzyme (ACE) inhibitors; however, treatment was not assessed in either study. Human pathogenic coronaviruses (severe acute respiratory syndrome coronavirus [SARS CoV] and SARSCoV 2) bind to their target cells through angiotensin converting enzyme 2 (ACE2) which is expressed by epithelial cells of the lung, intestine, kidney, and blood vessels. The expression of ACE2 is substantially increased in patients with type 1 or type 2 diabetes, who are treated with ACE inhibitors and angiotensin II type I receptor blockers (ARBs) Hypertension is also treated with ACE inhibitors and ARBs, which results in an upregulation of ACE2. ACE2 can also be increased by thiazolidinediones and ibuprofen. These data suggest that ACE2 expression is increased in diabetes and treatment with ACE inhibitors and ARBs increases ACE2 expression. Consequently, the increased expression of ACE2 would facilitate infection with COVID 19. We therefore hypothesise that diabetes and hypertension treatment with ACE2 stimulating drugs increases the risk of developing severe and fatal COVID 19. If this hypothesis were to be confirmed, it could lead to a conflict regarding treatment because ACE2 reduces inflammation and has been suggested as a potential new therapy for inflammatory lung diseases, cancer, diabetes, and hypertension. A further aspect that should be investigated is the genetic predisposition for an increased risk of SARS CoV 2 infection, which might be due to ACE2 polymorphisms that have been linked to diabetes mellitus, cerebral stroke, and hypertension, specifically in Asian populations. Summarising this information, the sensitivity of an individual might result from a combination of both therapy and ACE2 polymorphism. We suggest that patients with cardiac diseases, hypertension, or diabetes, who are treated with ACE2increasing drugs, are at higher risk for severe COVID 19 infection and, therefore, should be monitored for ACE2 modulating medications, such as ACE inhibitors or ARBs. Based on a PubMed search on Feb 28, 2020, we did not find any evidence to suggest that antihypertensive calcium channel blockers increased ACE2 expression or activity, therefore these could be a suitable alternative treatment in these patients. We declare no competing interests.
A Dataset and Taxonomy for Urban Sound Research
Venue: ACM Multimedia
Year: 2014

Automatic urban sound classification is a growing area of research with applications in multimedia retrieval and urban informatics. In this paper we identify two main barriers to research in this area the lack of a common taxonomy and the scarceness of large, real world, annotated data. To address these issues we present a taxonomy of urban sounds and a new dataset, UrbanSound, containing 27 hours of audio with 18.5 hours of annotated sound event occurrences across 10 sound classes. The challenges presented by the new dataset are studied through a series of experiments using a baseline classification system.