nils-herrmann/clean_scirepeval huggingface dataset:
A study of density grid based clustering algorithms on data streams
Venue: 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)
Year: 2011

Clustering data streams attracted many researchers since the applications that generate data streams have become more popular. Several clustering algorithms have been introduced for data streams based on distance which are incompetent to find clusters of arbitrary shapes and cannot handle the outliers. Density based clustering algorithms are remarkable not only to find arbitrarily shaped clusters but also to deal with noise in data. In density based clustering algorithms, dense areas of objects in the data space are considered as clusters which are segregated by low density area. Another group of the clustering methods for data streams is grid based clustering where the data space is quantized into finite number of cells which form the grid structure and perform clustering on the grids. Grid based clustering maps the infinite number of data records in data streams to finite numbers of grids. In this paper we review the grid based clustering algorithms that use density based algorithms or density concept for the clustering. We called them density grid clustering algorithms. We explore the algorithms in details and the merits and limitations of them. The algorithms are also summarized in a table based on the important features. Besides that, we discuss about how well the algorithms address the challenging issues in the clustering data streams.
Two tales of earnings management with short sales deregulation
Year: 2020

We study the impact of short sales on accrual based and real earnings management (EM) Based on the costs and benefits of using EM to hide negative information, we derive an analytical model showing that there are two possibilities: (1) a firm engages in less accrual based and real EM when facing short seller scrutiny (the informational efficiency hypothesis) or (2) a firm switches from accrual based EM (a less sophisticated method) to real EM (a more sophisticated method) which we call the sophisticated information hiding hypothesis. That is, there is a tradeoff between accrual based and real EM in the presence of short sales. Using a natural experiment of the recent short sales deregulation in China, we show findings consistent with the latter reaction. Additional analysis suggests that the decrease in accrual based EM and increase in real EM are driven primarily by firms with non Big 10 auditors or firms not under shareholder or regulatory scrutiny. We interpret the findings as being consistent with the model prediction that for firms with weak inside and outside monitoring, the probability of detecting real EM is low, and thus the tradeoff between accrual based and real EM prevails in the presence of short sales.
Forty years of wicked problems literature: forging closer links to policy studies
Year: 2019

Rittel and Webber boldly challenged the conventional assumption that 'scientific' approaches to social policy and planning provide the most reliable guidance for practitioners and researchers who are addressing complex, and contested, social problems. This provocative claim, that scientific technical approaches would not 'work' for complex social issues, has engaged policy analysts, academic researchers and planning practitioners since the 1970s. Grappling with the implications of complexity and uncertainty in policy debates, the first generation of 'wicked problem' scholars generally agreed that wicked issues require correspondingly complex and iterative approaches. This tended to quarantine complex 'wicked' problems as a special category that required special collaborative processes. Most often they recommended the inclusion of multiple stakeholders in exploring the relevant issues, interests, value differences and policy responses. More than four decades later, however, there are strong arguments for developing a second generation approach which would 'mainstream' the analysis of wicked problems in public policy. While continuing to recognize the centrality of complexity and uncertainty, and the need for creative thinking, a broader approach would make better use of recent public policy literatures on such topics as problem framing, policy design, policy capacity and the contexts of policy implementation.
SWATH MS based quantitative proteomics analysis to evaluate the antileishmanial effect of Commiphora wightii "Guggul" and Amphotericin B on a clinical isolate of Leishmania donovani.
Venue: Journal of proteomics
Year: 2020

The present study provides comprehensive proteomics analyses of the response of L. donovani parasite to pharamacological stress in vitro. Identification of differentially expressed proteins with associated molecular functions and metabolic pathways, clearly provides an insight into the potential mechanism of the antileishmanial effects as well as a comparative response of the parasite to Guggul and AmB. Treatment of parasite with AmB results in an enhanced modulatory mechanism to counteract the drug induced stress which may have contributed to relapse. In case of Guggul treatment, an effective antipromastigote activity was observed which is being reported for the first time. Thus, a deeper understanding of the molecular pathways in the Leishmania parasite in response to pharmacological stress would help in designing novel and effective strategies in targeting the key molecules essential for parasite survival. It will also help in screening of new lead molecules targeting these vital pathways which could be used as an adjunct therapy along with the limited repertoire of antileishmanial drugs.
Hybridizing d type NaxV2O5*nH2O with graphene towards high performance aqueous zinc ion batteries
Venue: Electrochimica Acta
Year: 2019

Thanks to low cost and high safety, aqueous zinc ion batteries (AZIBs) are attractive candidates for large scale energy storage applications, while suitable cathode materials are needed urgently. In this work, d NaxV2O5*nH2O with a large interlayer spacing of 10.6 A is reported as the cathode material for aqueous zinc ion batteries for the first time. It is found that d NaxV2O5*nH2O performs better than Na2V6O16*nH2O under the same condition, and its electrochemical performances can be significantly improved after hybridizing it with reduced graphene oxide. The obtained nanocomposite can deliver high reversible capacity of 433.5 mAh g 1 at 0.1 A g 1, superior rate capability of 244.1 mAh g 1 at 5 A g 1, and good cyclability of 70.5% over 1000 cycles. Such great performances origin from the synergetic effect of d NaxV2O5*nH2O and graphene, which enables rapid Zn2+ diffusion and large capacitive contribution. Besides, the ex situ measurement results demonstrate good structural stability and reversible Zn2+ ion storage behavior of reduced graphene oxide/d NaxV2O5*nH2O nanocomposite. This work extends the knowledge into the material technology of AZIBs.
Stakeholders' perspective about their engagement in developing a competency based nursing baccalaureate curriculum: A qualitative study.
Venue: Journal of professional nursing official journal of the American Association of Colleges of Nursing
Year: 2020

Stakeholder engagement is the basis of an emerging and innovative educational model called competency based education. However, although several studies have analysed the stakeholders' perspective in nursing, few studies have analysed the stakeholders' perspective in competence based curriculum design. Thus, the aim of this study was to analyse the opinions and perspectives of stakeholders about the development of a competency based baccalaureate nursing curriculum with stakeholder engagement.  A phenomenological study was conducted. This method combines descriptive features (Husserlian) and interpretive phenomenology (Gadamerian) The interviews were ended when data saturation was achieved, specifically the redundancy of themes.  The content analysis identified three main categories: (1) a "bridge" that merges education and the work context, (2) stakeholder engagement a contentious issue; and (3) stakeholder engagement structuring a methodology.  Through the stakeholder engagement, university could have a constant interaction between the didactics and professional practice and could improve professional identity and job satisfaction among nurses.
Representation of features as images with neighborhood dependencies for compatibility with convolutional neural networks
Venue: Nature communications
Year: 2020

Deep learning with Convolutional Neural Networks has shown great promise in image based classification and enhancement but is often unsuitable for predictive modeling using features without spatial correlations. We present a feature representation approach termed REFINED (REpresentation of Features as Images with NEighborhood Dependencies) to arrange high dimensional vectors in a compact image form conducible for CNN based deep learning. We consider the similarities between features to generate a concise feature map in the form of a two dimensional image by minimizing the pairwise distance values following a Bayesian Metric Multidimensional Scaling Approach. We hypothesize that this approach enables embedded feature extraction and, integrated with CNN based deep learning, can boost the predictive accuracy. We illustrate the superior predictive capabilities of the proposed framework as compared to state of the art methodologies in drug sensitivity prediction scenarios using synthetic datasets, drug chemical descriptors as predictors from NCI60, and both transcriptomic information and drug descriptors as predictors from GDSC.
Predicting the Price of Bitcoin Using Hybrid ARIMA and Machine Learning
Venue: FDSE
Year: 2019

Bitcoin is one of the most popular cryptocurrencies in the world, has attracted broad interests from researchers in recent years. In this work, Autoregressive Integrate Moving Average (ARIMA) model and machine learning algorithms will be implemented to predict the closing price of Bitcoin the next day. After that, we present hybrid methods between ARIMA and machine learning to improve prediction of Bitcoin price. Experiment results showed that hybrid methods have improved accuracy of predicting through RMSE and MAPE.
Cochlear Implant Therapy Improves the Quality of Life in Older Patients A Prospective Evaluation Study.
Venue: Otology neurotology official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
Year: 2020

To determine the effects of cochlear implant (CI) hearing rehabilitation on quality of life in older patients =65 yr) STUDY DESIGN Prospective observational study.  Department of Oto Rhino Laryngology, Medical University Frankfurt/Main.  Patients aged between 65 and 86 years who received unilateral CI therapy for the first time.  Unilateral cochlear implantation.  In addition to audiological parameters, the World Health Organization Quality of Life Scale old (WHOQL OLD) was used to assess quality of life prior to surgery, at the time of first fitting of the audio processor (approx. 1 mo after surgery) and 6 months afterward. Dementia and depression were excluded using dementia detection test (DemTect) and geriatric depression scale.  Speech recognition improved significantly during the study period. Furthermore, the total WHOQL OLD score showed a significant improvement of quality of life comparing the preoperative and the 6 months data (60.0 15.7 to 66.8 12.2 points) (p 0.001) Only 6 months after surgery, comparable quality of life values were achieved compared to the corresponding population average of the same age group (67.96 14.74 points) No statistically significant difference remained between the study group and the age adjusted population average (p 0.37)  To achieve auditory rehabilitation, CI treatment in older patients can be strongly recommended, not only hearing rehabilitation, but also to improve quality of life.
Classification of Dynamic Contrast Enhanced MR Images of Cervical Cancers Using Texture Analysis and Support Vector Machines
Venue: IEEE Transactions on Medical Imaging
Year: 2014

Dynamic contrast enhanced MRI (DCE MRI) provides insight into the vascular properties of tissue. Pharmacokinetic models may be fitted to DCE MRI uptake patterns, enabling biologically relevant interpretations. The aim of our study was to determine whether treatment outcome for 81 patients with locally advanced cervical cancer could be predicted from parameters of the Brix pharmacokinetic model derived from pre chemoradiotherapy DCE MRI. First order statistical features of the Brix parameters were used. In addition, texture analysis of Brix parameter maps was done by constructing gray level co occurrence matrices (GLCM) from the maps. Clinical factors and first and second order features were used as explanatory variables for support vector machine (SVM) classification, with treatment outcome as response. Classification models were validated using leave one out cross model validation. A random value permutation test was used to evaluate model significance. Features derived from first order statistics could not discriminate between cured and relapsed patients (specificity 0% 20% p values close to unity) However, second order GLCM features could significantly predict treatment outcome with accuracies ~70% similar to the clinical factors tumor volume and stage (69% The results indicate that the spatial relations within the tumor, quantified by texture features, were more suitable for outcome prediction than first order features.
Towards Informed Exploration for Deep Reinforcement Learning
Year: 2019

Author(s) Tang, Haoran Advisor(s) Sethian, James A; Abbeel, Pieter  In this thesis, we discuss various techniques for improving exploration for deep reinforcement learning. We begin with a brief review of reinforcement learning (RL) and the fundamental v.s. exploitation trade off. Then we review how deep RL has improved upon classical and summarize six categories of the latest exploration methods for deep RL, in the order increasing usage of prior information. We then explore representative works in three categories discuss their strengths and weaknesses. The first category, represented by Soft Q learning, uses regularization to encourage exploration. The second category, represented by count based via hashing, maps states to hash codes for counting and assigns higher exploration to less encountered states. The third category utilizes hierarchy and is represented by modular architecture for RL agents to play StarCraft II. Finally, we conclude that exploration by prior knowledge is a promising research direction and suggest topics of potentially impact.
A smooth broadcasting scheme for VBR encoded hot videos
Venue: Comput. Commun.
Year: 2006

One way of broadcasting a popular video is partitioning the video into segments, each being broadcasted on several streams periodically. The approach alleviates the bandwidth thirsty in real time video broadcasting without sacrificing viewers' waiting time by allowing multiple users to share the same video segments. One representative scheme of the category is the recursive frequency splitting (RFS) broadcasting scheme, which yields approximate minimum waiting time. In this paper, a novel approach is introduced to enhance RFS, called Smooth RFS (SRFS) in which the approaches of segment patching and asynchronous downloading playing are proposed for achieving a smooth broadcast of variable bit rate (VBR) encoded videos. The design of SRFS aims to reduce the peak bandwidth consumption and variance during the distribution of VBR videos in order to achieve better upper bounds on the bandwidth peak and the variance. Extensive simulation has been conducted on the proposed scheme by comparing a number of past reported counterparts, including the trace adaptive fragmentation (TAF) scheme and the smooth fast broadcasting (SFB) scheme. The results indicate that the proposed scheme yields lower bandwidth peak and variance. Besides, given a fixed bandwidth that is smaller than the peak, SRFS obtains a much smaller blocking rate than that of the other schemes.
A System of Three Super Earths Transiting the Late K Dwarf GJ 9827 at 30 pc
Year: 2018

We report the discovery of three small transiting planets orbiting GJ 9827, a bright (K 7.2) nearby late K type dwarf star. GJ 9827 hosts a 1.62 0.11 R super Earth on a 1.2 day period, a 1.269^+0.087)_( 0.089) R super Earth on a 3.6 day period, and a 2.07 0.14 R super Earth on a 6.2 day period. The radii of the planets transiting GJ 9827 span the transition between predominantly rocky and gaseous planets, and GJ 9827 b and c fall in or close to the known gap in the radius distribution of small planets between these populations. At a distance of 30 pc, GJ 9827 is the closest exoplanet host discovered by K2 to date, making these planets well suited for atmospheric studies with the upcoming James Webb Space Telescope. The GJ 9827 system provides a valuable opportunity to characterize interior structure and atmospheric properties of coeval planets spanning the rocky to gaseous transition.
Post traumatic Focal Adhesive Arachnoiditis
Venue: Journal of the Belgian Society of Radiology
Year: 2017

referred for magnetic resonance imaging (MRI) of the thoracic spine due to longstanding walking difficulties. His complaints started shortly after he was beaten with a baseball bat in the region of his back. On admission, the patient suffered from disturbed walking scheme with bilateral spastic hypertonia and reduced muscle strength of the lower limbs. Further neurological examination was unremarkable, while laboratory findings were within the range of normal limits. MRI examination showed widespread intradural bands of low T2 signal (Figure 1A C, arrows) showing vivid enhancement (Figure 1D and E, arrows) There was distortion of the thoracic spinal cord, especially at Th7/8 level where the cord was displaced posteriorly (Figure 2A and B, arrows) At this level, the spinal cord showed marked T2 hyperintense signal in keeping with myelomalacia (Figure 2A C, arrowheads) There was cord atrophy below the level of Th8 extending to the conus medullaris (Figure 2A, asterisk) Based on imaging and clinical findings, the diagnosis of post traumatic focal adhesive arachnoiditis was made.
Exploring Driving aware Salient Object Detection via Knowledge Transfer
Venue: 2021 IEEE International Conference on Multimedia and Expo (ICME)
Year: 2021

Recently, general salient object detection (SOD) has made great progress with the rapid development of deep neural networks. However, task aware SOD has hardly been studied due to the lack of task specific datasets. In this paper, we construct a driving task oriented dataset where pixel level masks of salient objects have been annotated. Comparing with general SOD datasets, we find that the cross domain knowledge difference and task specific scene gap are two main challenges to focus the salient objects when driving. Inspired by these findings, we proposed a baseline model for the driving task aware SOD via a knowledge transfer convolutional neural network. In this network, we construct an attentionbased knowledge transfer module to make up the knowledge difference. In addition, an efficient boundary aware feature decoding module is introduced to perform fine feature decoding for objects in the complex task specific scenes. The whole network integrates the knowledge transfer and feature decoding modules in a progressive manner. Experiments show that the proposed dataset is very challenging, and the proposed method outperforms 12 state of the art methods on the dataset, which facilitates the development of task aware SOD.
Evaluation the effect of individual and demographic factors on awareness attitude and performance of radiographers regarding principles of radiation protection
Year: 2016

In modern medicine, the use of ionizing radiation for diagnosis and treatment of diseases is increasing; on the other hand, harmful effects of this radiation for human have been demonstrated. Radiographers have vital role in application of principles of radiation protection and they can reduce unwanted exposure.  Therefore, understanding the factors influencing awareness, attitudes and performance of radiographers regarding radiation protection principles was assessed by three special questionnaires.  The level of awareness, attitude and performance of radiographers regarding principles of radiation protection were 4.3% 65.4% and 1.08% respectively. Results showed that there is a significant difference between attitudes of the radiographers with high level of education and other groups. The level of education and training affects the attitudes, awareness and performance regards principles of radiation protection.  So, to improve the level of awareness, attitude and performance of radiographers, it seems that the radiographers must spend retraining courses about radiation protection and technical issues; moreover, supervision and inspection authorities must be increased.  Radiographers, Radiation protection, Awareness, Attitude, Performance.
Residuos solidos en Mar del Plata: un analisis desde la contabilidad social y ambiental
Year: 2020

El Municipio del Partido de General Pueyrredon, es el encargado de la recoleccion de residuos solidos urbanos. La misma se realiza a traves de una empresa privada mediante licitacion publica internacional. Este servicio incluye la recoleccion de residuos solidos domiciliarios que deben ser separados en origen y de poda, el barrido de calles y avenidas y la limpieza de playas publicas no concesionadas Los residuos son transportados al Area de Disposicion Final de Residuos del Partido. Aquellos que son separados en origen se dirigen a la Instalacion de Recuperacion de Materiales IRM operada por recuperadores pertenecientes a la Cooperativa Comun Unidad de Recuperadores Argentinos CURA Aunque, no todos los residuos solidos llegan al destino de la planta de recuperacion, sino que una gran cantidad de residuos reciclables no son recuperados al no ser separados en origen, otros son desplazados por el agua de las lluvias desde las calles de la ciudad hacia el mar y suelen terminar en las orillas de la playa. Esto afecta el patrimonio ambiental que posee la ciudad, generando principalmente un perjuicio en las condiciones naturales del mar y, consecuentemente, en el turismo que es la principal actividad de la ciudad La acumulacion de desechos en vertederos o rellenos sanitarios genera graves problemas al medio ambiente, debido a que no se le realiza ningun tratamiento al residuo ni tampoco hay recuperacion de energia. En resumen, los residuos solidos que no son tratados generan contaminacion del aire, napas y ecosistemas terrestres Es necesario contar con informacion cualitativa y cuantitativa sobre este impacto negativo al medio ambiente, que sea de utilidad para la toma de decisiones que contribuyan al uso sustentable y sostenible de los recursos naturales. En ese sentido, creemos que es nuestra responsabilidad poner la contabilidad al servicio del medio ambiente. La Contabilidad Ambiental puede definirse como "La parte de la Contabilidad aplicada cuyo objeto son las relaciones entre una entidad y su medio ambiente, lo cual requiere precisar tanto el concepto de entidad como el de medio ambiente. El medio ambiente de una entidad puede definirse como su entorno natural, o bien como su entorno vital, abarcando, en este segundo caso, el entorno natural, cultural y social de la entidad a lo largo de un determinado periodo de tiempo" (Fernandez Cuesta, 2004, p. 33) El presente trabajo tiene como objeto analizar la Gestion de Residuos Solidos en la ciudad de Mar del Plata y su impacto al medioambiente desde la perspectiva de la Contabilidad Social y Ambiental. En la primer parte del mismo nos proponemos caracterizar a la ciudad de Mar del Plata, su sistema de gestion de residuos y la normativa aplicable en general y en especifico la aplicable a nivel municipal. Luego de ello, analizaremos algunos conceptos de la Contabilidad Ambiental para finalizar aplicandolos al caso particular.