nils-herrmann/clean_scirepeval huggingface dataset:
Changes to the chemical state of the Northern Hemisphere atmosphere during the second half of the twentieth century
Year: 2016

The NOx (NO and NO2) and HOx (OH and HO2) budgets of the atmosphere exert a major influence on atmospheric composition, controlling removal of primary pollutants and formation of a wide range of secondary products, including ozone, that can influence human health and climate. However, there remain large uncertainties in the changes to these budgets over recent decades. Due to their short atmospheric lifetimes, NOx and HOx are highly variable in space and time, and so the measurements of these species are of limited value for examining long term, large scale changes to their budgets. Here, we take an alternative approach by examining long term atmospheric trends of alkyl nitrates, the production efficiency of which is dependent on the atmospheric [NO] [HO2] ratio. We derive long term trends in the alkyl nitrates from measurements in firn air from the NEEM site, Greenland. Their mixing ratios increased by a factor of 3 5 between the 1970s and 1990s. This was followed by a steep decline to the sampling date of 2008. Moreover, we examine how the trends in the alkyl nitrates compare to similarly derived trends in their parent alkanes (i.e. the alkanes which, when oxidised in the presence of NOx, lead to the formation of the alkyl nitrates) The ratios of the alkyl nitrates to their parent alkanes increased from around 1970 to the late 1990s. This is consistent with large changes to the [NO] [HO2] ratio in the Northern Hemisphere atmosphere during this period. Alternatively, they could represent changes to concentrations of the hydroxyl radical, OH, or to the transport time of the air masses from source regions to the Arctic.
"Comparisons are Odious?" Revisiting the ancient fable of the ant and the grasshopper adapted in Maugham's short story
Year: 2019

The article seeks to locate a comparative study of the meanings and the morals of a popular ancient fable, adapted by William Somerset Maugham in his short story, The Ant and the Grasshopper. The comparison and contrast in adapting the fable generated an intense academic debate about the appropriate policies of life, a human should undergo. Alike the ancient fable, the setting of the story opens with the conversation between an industrious ant and its reluctant counterpart, a grasshopper. Although the story of the fable is embodied with a moral where industry is rewarded and giddiness punished, we see a completely different scenario at the end of the story. Therefore, it is an irony of the moral conflict between two Ramsay brothers, namely George Ramsay, a man of ethics and Tom Ramsay, a man of a fantasy world. Throughout the story, The Ant and the Grasshopper, Maugham's effort to portray the themes of justice, trust, fear, morality, embarrassment, happiness and struggle is indeed praiseworthy. But, at the same time, it has aroused a hypothesis of seeking out the ultimate principles of life. The paper considers the development of the Greek fable from its origin to the later adaptations, including the version of La Fontaine, a French fabulist, and the final reversal to a counter fable by Maugham. It also includes a web of researches in the corresponding fields, and a synthesis resulting from the causes and effects of indebtedness and unemployment that can eventually affect the economy through fluctuations in confidence. The further objective of this work illustrates the misconception and mockery of a man of letter and the eventual paradoxes he has to face in reality. Finally, it concludes with an inception that a post modern world like ours needs not only a determined and preset humane policy, but also a new narrative, and liberal outlook to survive or live in luxury.
COMPUTATIONAL ANALYSIS OF DEEP LEARNING MODELS FOR CLASSIFICATION OF EEG DATA RELATED TO COGNITIVE IMPAIRMENT
Year: 2020

Deep Learning models are proven to be computationally extensive and produce good analytical results. EEG (electroencephalography) is the technique by which the electrical activities of the brain can be recorded which when studied properly can give useful insights and can be used to diagnose various neurological diseases. In this paper we have systematically reviewed the literature wherein different deep learning strategies like Convolutional Neural Network, Recurrent Neural Network, Multi layered perceptron, and Deep belief networks are used to classify the EEG signals. This review paper has mainly covered the prominent research work done in the classification of EEG for various purposes like the classification of motor Imagery for BCI, Classifying EEG signals for early detection of (MCI)Mild Cognitive Impairment, AD (Alzheimer Disease) Seizure Epilepsy etc. The comparative analysis of these algorithms and their research work based on their pertinent features is done along with their associated outcomes which are presented in the tabulated format. We showed why EEG is better and efficient than MRI the advantages of EEG over MRI. The field has diverse research records so far but it has to be studied further to make most out of the capabilities of deep learning algorithms. In our study, CNN was found to yield the best results for the classification as compared to other deep learning strategies. Further, we implemented the basic models of CNN, RNN, MLP for the binary classification of a seizure data and did a comparative analysis of their performances. The results showed that 1 D CNN (Model 3) gave the highest accuracy of 98.5% among the other two models. This paper will be very encouraging and helpful to those who are willing to do research in this field wish to look upon the previous research in this field.
Global consolidation of industries and business failures: insights from brick and mortar and online outlets
Year: 2017

Although online platforms are increasingly seen as a linchpin for firms competing in the 21st century, our understanding of competition between the traditional brick and mortar and online outlets, and how this can lead to different types of business failures, remains limited. In the light of the disjointed nature of the current streams of research, we propose an integrated framework that classifies the differential effects of online and brick and mortar competition. Based on a review of the literature, the study identified four competitive dynamics, i.e. bricks vs. bricks, clicks vs. bricks, clicks vs. clicks and brick and click, and explores how they can lead to different kinds of business. It is contended that the failure rate is likely to rise for small firms that adopt a sole brick and mortar strategy largely due to the risk of becoming 'research shops' The study contributes to comparative strategic management literature by shedding light on the evolution of online and offline management strategies and practices across the globe. In this direction, the study provides insights on some aspects both universal and country specific features in the evolution of online and offline. The analysis highlights the importance of championing successful blending of both online and offline platforms.
The electric field alignment of short carbon fibres to enhance the toughness of epoxy composites
Year: 2018

An investigation is presented on increasing the fracture toughness of epoxy/short carbon fibre (SCF) composites by alignment of SCFs using an externally applied alternating current (AC) electric field. Firstly, the effects of SCF length, SCF content and AC electric field strength on the rotation of the SCFs suspended in liquid (i.e. uncured) epoxy resin are investigated. Secondly, it is shown the mode I fracture toughness of the cured epoxy composites increases with the weight fraction of SCFs up to a limiting value (5 wt% Thirdly, the toughening effect is greater when the SCFs are aligned in the composite normal to the direction of crack growth. The SCFs increases the fracture toughness by inducing multiple intrinsic and extrinsic toughening mechanisms, which are identified. Based on the identified toughening mechanisms, an analytical model is proposed to predict the enhancement to the fracture toughness due to AC electric field alignment of the SCFs.
Global Context Aware Progressive Aggregation Network for Salient Object Detection
Venue: AAAI
Year: 2020

Deep convolutional neural networks have achieved competitive performance in salient object detection, in which how to learn effective and comprehensive features plays a critical role. Most of the previous works mainly adopted multiple level feature integration yet ignored the gap between different features. Besides, there also exists a dilution process of high level features as they passed on the top down pathway. To remedy these issues, we propose a novel network named GCPANet to effectively integrate low level appearance features, high level semantic features, and global context features through some progressive context aware Feature Interweaved Aggregation (FIA) modules and generate the saliency map in a supervised way. Moreover, a Head Attention (HA) module is used to reduce information redundancy and enhance the top layers features by leveraging the spatial and channel wise attention, and the Self Refinement (SR) module is utilized to further refine and heighten the input features. Furthermore, we design the Global Context Flow (GCF) module to generate the global context information at different stages, which aims to learn the relationship among different salient regions and alleviate the dilution effect of high level features. Experimental results on six benchmark datasets demonstrate that the proposed approach outperforms the state of the art methods both quantitatively and qualitatively.
Cardioband system as a treatment for functional mitral regurgitation
Venue: Expert review of medical devices
Year: 2018

Are the current data on the Cardioband in the clinical area enough to consider it a tool for mitral regurgitation treatment? Severe secondary mitral valve insufficiency frequently affects high risk surgical patients. The Cardioband system is a novel percutaneous surgical like device for direct annuloplasty. It is implanted into the beating heart by transvenous femoral access, with minimal impact on hemodynamic and cardiac function during implantation. So far, it has demonstrated safety and feasibility in high risk patients with functional mitral regurgitation; it has imparted significant annular reduction and regurgitation improvements. In well selected patients, it could be an option for mitral valve repair.  This is a bibliographic review based on scientific publications and medical congress reports. It includes the most current information related to Cardioband in mitral regurgitation.  This novel, less invasive and effective tool is an option for the open repair or replacement of the mitral valve in high risk surgical patients. Although the current results of Cardioband are promising, more data and longer follow up times are necessary to confirm its safety and efficacy and to evaluate the durability of the results.
Water Quality Monitoring System Using WSN in Tanga Lake
Venue: DepCoS RELCOMEX
Year: 2019

Continuous Lake water quality monitoring is an important tool to a different aspect which includes catchment management authorities, providing real time data for environmental protection and tracking pollution sources in lakes around ANNABA reagent. In order to assist catchment managers to maintain the health of aquatic ecosystems taking into consideration a cost effective water quality data collection a low cost low power system is proposed. The proposed system is constituted by spreading the sensor nodes and the base station. The nodes and base stations are linked using WSN technology (e.g. Zigbee) Base stations will be connected to the Internet using the Ethernet shield. The results indicate that a reliable monitoring system can be designed with appropriate calibration of sensors; this will allow us to continue monitoring the quality of the water at higher spatial resolution.
Effects of tea polyphenols and gluten addition on in vitro wheat starch digestion properties.
Venue: International journal of biological macromolecules
Year: 2019

Starch containing food normally has complex components and structure, which control its digestion kinetic properties and nutritional value. However, interactions among multiple food components and their effects on starch digestion kinetics are rarely reported. Here, we evaluated the influence of tea polyphenols [i.e. epigallocatechin (EGC) and epigallocatechin 3 gallate (EGCG) on the in vitro digestion rate and extent of wheat starch in the presence of gluten under uncooked and cooked conditions. The addition of EGC (20% starch basis) did not change the starch digestion rate and extent for both uncooked and cooked physical forms in the presence and absence of gluten, whereas EGCG (20% starch basis) significantly reduced the digestion extent of wheat starch by 25 30% in the absence of gluten and by 6.6 18.5% in the presence of gluten, a phenomenon that was caused by the reduced effective EGCG due to its interaction with gluten.
ENGINEERING PARAMETERS OF RECYCLED POLYSTYRENE CONCRETE MIXTURES
Venue: Misr Journal of Agricultural Engineering
Year: 2019

The effect of waste polystyrene aggregate (which used for packing of electrical devices and food packing) on concrete density, water absorption, compressive strength and thermal conductivity was investigated. Deferent concrete mixtures were made by replacing the sand content by polystyrene aggregate with different volumes (namely, 0% 5% 10% 15% 30% 70% and 100% in concrete with three cement content (300, 450 and 600 kg/m3) The density, water absorption and compressive strength of polystyrene concrete decreased with the increase of polystyrene aggregate. Results showed that the use of polystyrene aggregate in in concrete mixtures caused an increase in water absorption from 1.9% to 9.5% at different polystyrene aggregate ratio. The compressive strength reduced by ratio by 75% at polystyrene aggregate replacement ratio100% Thermal conductivity of polystyrene concrete mixtures decreased from 0.9 to 0.24 W/m.K with the increasing of polystyrene sand ratio up to 100%
One Network Adversarial Fairness
Venue: AAAI
Year: 2019

There is currently a great expansion of the impact of machine learning algorithms on our lives, prompting the need for objectives other than pure performance, including fairness. Fairness here means that the outcome of an automated decisionmaking system should not discriminate between subgroups characterized by sensitive attributes such as gender or race. Given any existing differentiable classifier, we make only slight adjustments to the architecture including adding a new hidden layer, in order to enable the concurrent adversarial optimization for fairness and accuracy. Our framework provides one way to quantify the tradeoff between fairness and accuracy, while also leading to strong empirical performance.
British girls' comics: An interview with Wilf Prigmore
Venue: Studies in Comics
Year: 2019

Wilf Prigmore worked at Fleetway/IPC in the 1970s. He was group editor for Girls' Adventure Comics, co creator of Misty (1978 80) and editor of Tammy (1971 84) amongst many other roles. The following interview is taken from conversations with Wilf by telephone, e mail and in person, between November 2016 and December 2019.
Robust Optimization for Deep Regression
Venue: 2015 IEEE International Conference on Computer Vision (ICCV)
Year: 2015

Convolutional Neural Networks (ConvNets) have successfully contributed to improve the accuracy of regression based methods for computer vision tasks such as human pose estimation, landmark localization, and object detection. The network optimization has been usually performed with L2 loss and without considering the impact of outliers on the training process, where an outlier in this context is defined by a sample estimation that lies at an abnormal distance from the other training sample estimations in the objective space. In this work, we propose a regression model with ConvNets that achieves robustness to such outliers by minimizing Tukey's biweight function, an M estimator robust to outliers, as the loss function for the ConvNet. In addition to the robust loss, we introduce a coarse to fine model, which processes input images of progressively higher resolutions for improving the accuracy of the regressed values. In our experiments, we demonstrate faster convergence and better generalization of our robust loss function for the tasks of human pose estimation and age estimation from face images. We also show that the combination of the robust loss function with the coarse to fine model produces comparable or better results than current state of the art approaches in four publicly available human pose estimation datasets.
AJEG BALI:POLITIK IDENTITAS DAN IMPLEMENTASINYA PADA BERBAGAI AGEN SOSIALISASI DI DESA PAKRAMAN UBUD, GIANYAR, BALI
Year: 2012

Bali is known as a very popular tourist destination area, not only in Indonesia but also overseas. The tourism is supported by the cultural identity of Balinese ethnic, its customs and culture which are based on the values of Hinduism and Tri Hita Karana philosophy. The sociocultural change which is an impact of modernization, globalization, tourism growth and the inflow of other ethnics threatens the identity of Balinese ethnic. It has developed a politics of identity known as Ajeg Bali.Desa Pakraman is a traditional institution that becomes the basis of implementation and the agent of socialization of Ajeg Bali movement. It has many social and religious institutions that are considered as a cultural twist of Balinese culture. Desa Pakraman Ubud is well known as 'kampung global' (global village) In relation to the cultural and tourism identity preserve, Desa Pakraman Ubud applies the politics of identity of Ajeg Bali movement. Related to these reasons, this research focuses on some problems: (1) Why does the community of Desa Pakraman Ubud carry out the retention of ethnic identity through the politics of identity of Ajeg Bali movement? (2) What is the pattern of the retention of ethnic identity through Ajeg Bali in Desa Pakraman Ubud? (3) What is the implication of the retention of ethnic identity through Ajeg Bali toward inter ethnic relations in Desa Pakraman Ubud?This study employs qualitative research with an ethnography approach. The site of this research is Desa Pakraman Ubud, Gianyar, Bali. The data were collected from interview, direct observation to the site, and document analysis. The data were analyzed by considering emic and etic perspektives. The results of the study demonstrates that the practice of the politics of identity of Ajeg Bali movement in Desa Pakraman Ubud emerges as a retention of cultural identity of Balinese ethnic towards the politics of culture from Orde Baru, modernization, globalization, and a retention toward the non Balinese ethnic. The politics of identity of Ajeg Bali movement takes place in kuren and dadia, desa pakraman, desa dinas, subak, sekaa, puri and geriya for informal education. On the contrary, it takes place in schools for formal education. For non formal education, it occurs in mass media. The application of this movement has an implication to an affirmation of desa pakraman's position and the inter ethnic relations which bring an ethnocentrism concept, stereotype and ethnic prejudice. It also causes an implication on associative, dissociative and adaptive social process. Ajeg Bali, politics of identity, retention of ethnic identity, agents of socialization
Node to Node Secure Data Communication for IoT Devices Using Diffie Hellman, AES, and MD5 Cryptographic Schemes
Venue: 2019 International Conference on Cyber Security and Internet of Things (ICSIoT)
Year: 2019

Identifying the right source and target nodes in IoT as well as secure data communication is very vital in ensuring security, validity and reliability of IoT communication. Since more devices are being programmed to exchange data and commands autonomously in IoT and wireless sensor networks, security and authenticity of such transmitted data is very crucial. This calls for strong security approaches to prevent both passive and active attackers against data communication. This work proposed a scheme for securing communication among IoT devices by applying Diffie Hellman encryption algorithm to authenticate the communicating nodes while using AES and MD5 to encrypt and validate the data transfer among the nodes.
A primer on partial least squares structural equation modeling (PLS SEM)
Year: 2013

With applications using SmartPLS (www.smartpls.com) the primary software used in partial least squares structural equation modeling (PLS SEM) this practical guide provides concise instructions on how to use this evolving statistical technique to conduct research and obtain solutions. Featuring the latest research, new examples, and expanded discussions throughout, the Second Edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.
Review of stochastic differential equations in statistical arbitrage pairs trading
Year: 2019

The use of stochastic differential equations offers great advantages for statistical arbitrage pairs trading. In particular, it allows the selection of pairs with desirable properties, e.g. strong mean reversion, and it renders traditional rules of thumb for trading unnecessary. This study provides an exhaustive survey dedicated to this field by systematically classifying the large body of literature and revealing potential gaps in research. From a total of more than 80 relevant references, five main strands of stochastic spread models are identified, covering the 'Ornstein Uhlenbeck model' 'extended Ornstein Uhlenbeck models' 'advanced mean reverting diffusion models' 'diffusion models with a non stationary component' and 'other models' Along these five main categories of stochastic models, we shed light on the underlying mathematics, hereby revealing advantages and limitations for pairs trading. Based on this, the works of each category are further surveyed along the employed statistical arbitrage frameworks, i.e. analytic and dynamic programming approaches. Finally, the main findings are summarized and promising directions for future research are indicated.
Performance Evaluation under an AFR Scheme CSMA/CA for HomePlug AV Supported in Bianchi's Model
Year: 2018

HPAV uses a new retransmission model of lost packages called Aggregation with Fragment Retransmission (AFR) which utilizes CSMA/CA as a mechanism to accessing the media. The main purpose of this paper is to assess the performance of a network supported in HPAV standard under the scheme AFR.  In this paper, the concept of saturation of throughput will be used for a finite number of stations For that matter, it is necessary to assume that the size of the package is fixed of bits to a rate of Mbps. Additionally, an adaptation to Bianchi's model was carried out adjusted to the MAC structure of HPAV, which allows to represent CSMA/CA as a Markov's chain in discrete time of two dimensions. All this is done in order to represent the back off procedure under a scheme DCF with saturated stations. Relevance of the Subject: AFR is a scheme that was proposed in order to achieve a high efficiency in the control layer of media access (MAC) based on CSMA/CA, and that, to date, has only been considered in Wireless networks supported in 802.11n. To date, similar works have not yet been found applicable to HPAV in the vast bibliographic sources.  Based on the obtained results, it was possible to observe that the model allows to assess the probability of lost packages, the MAC efficiency, the throughput and the delay levels in a PLC network, under a scheme AFR, subject to the number of stations, the size of the containment window and bandwidth available in the channel.  It is recommended to carry out similar studies under the use of TDMA over HPAV for the voice and video broadcasting, having into account that HPAV uses a mechanism of accessing to the hybrid media in order to offer adequate levels of QoS.