nils-herrmann/clean_scirepeval huggingface dataset:
Cooperative Watchdog for Malicious Failure Notification in Wireless Ad Hoc Networks
Venue: 2016 8th IFIP International Conference on New Technologies, Mobility and Security (NTMS)

For fault tolerant wireless ad hoc networks, detection and notification of failure of intermediate wireless nodes are critical. Until now, various failure detection and notification methods for recovery such as timeout and watchdog have been proposed for stop failure and Byzantine failure restricted to different data message transmissions. In order to avoid desperate cases such that correctly working wireless intermediate nodes are inappropriately taken away from the wireless multihop transmission routes due to malicious failure notification, this paper proposes a novel cooperative watchdog method. Here, not only the previous hop intermediate wireless nodes as in the conventional watchdog method but also another neighbor wireless node observe transmissions of both data messages and control messages such as failure notification to detect failure of an intermediate wireless node. This paper also proposes an ad hoc routing protocol to determine both a sequence of intermediate wireless nodes and additional observing wireless nodes for the cooperative watchdog. Simulation experiments show that the route detection ratio by the proposed routing protocol is a little lower than the well know ad hoc routing protocol AODV; however, performance of data message transmissions is never reduced since no additional control messages are usually transmitted in the proposed cooperative watchdog method.
Role of TLRs and DAMPs in allograft inflammation and transplant outcomes
Venue: Nature Reviews Nephrology

Graft inflammation impairs the induction of solid organ transplant tolerance and enhances acute and chronic rejection. Elucidating the mechanisms by which inflammation is induced after organ transplantation could lead to novel therapeutics to improve transplant outcomes. In this Review we describe endogenous substances damage associated molecular patterns (DAMPs) that are released after allograft reperfusion and induce inflammation. We also describe innate immune signalling pathways that are activated after solid organ transplantation, with a focus on Toll like receptors (TLRs) and their signal adaptor, MYD88. Experimental and clinical studies have yielded a large body of evidence that TLRs and MYD88 are instrumental in initiating allograft inflammation and promoting the development of acute and chronic rejection. Ongoing clinical studies are testing TLR inhibition strategies in solid organ transplantation, although avoiding compromising host defence to pathogens is a key challenge. Further elucidation of the mechanisms by which sterile inflammation is induced, maintained and amplified within the allograft has the potential to lead to novel anti inflammatory treatments that could improve outcomes for solid organ transplant recipients.
Dataset on protein composition of a human plasma sub proteome able to modulate the Dengue 2 virus infection in Huh 7.5 cells
Venue: Data in brief

The four serotypes of dengue virus (DENV1 4) are the causal agents of the emerging disease Dengue Fever and its severe forms. DENV is inoculated into human blood through a mosquito bite. Thus, plasma is an important media for DENV dissemination in infected persons and several important interactions should take place for the virus with human plasma proteins that strongly influence or may determine the course of the infection. This dataset contains 239 proteins identified in the elution fractions of human plasma subjected to DE 52 anion exchange chromatography. Data on DENV2 infection of Huh 7.5 cells in presence of the human plasma fraction is also presented.
Detecting privatization factors on promoting exports of steel companies

Received January 5, 2016 Received in revised format March 28, 2016 Accepted April 12, 2016 Available online April 14, 2016 Privatization is considered as the transfer of business from the government to the private sector. This process is often accomplished in an attempt to reduce the size of government, increase the productivity and export activities. There is no doubt that in an export oriented economy, government tries to promote expert based activities by making necessary changes on rules and regulations. This paper presents an empirical investigation to determine important factors on promoting export in Iran. The study designs a questionnaire in Likert scale and distributes it among some experts active in steel industry. Kaiser Meyer Olkin Measure of Sampling Adequacy is equal to 0.839 and Bartlett's Test of Sphericity yields an approximation Chi Square value of 2485.02 (Sig. 0.000, df 276) Using principle component analysis with Varimax rotation, the study has detected five important factors including human resources development, productivity management, marketing management, creating competitive environment and building necessary infrastructures, which influence the most on export activities.
Projection algorithms for nonconvex minimization with application to sparse principal component analysis
Venue: J. Glob. Optim.

We consider concave minimization problems over nonconvex sets. Optimization problems with this structure arise in sparse principal component analysis. We analyze both a gradient projection algorithm and an approximate Newton algorithm where the Hessian approximation is a multiple of the identity. Convergence results are established. In numerical experiments arising in sparse principal component analysis, it is seen that the performance of the gradient projection algorithm is very similar to that of the truncated power method and the generalized power method. In some cases, the approximate Newton algorithm with a Barzilai Borwein Hessian approximation and a nonmonotone line search can be substantially faster than the other algorithms, and can converge to a better solution.
Iron induced epigenetic abnormalities of mouse bone marrow through aberrant activation of aconitase and isocitrate dehydrogenase
Venue: International Journal of Hematology

Iron overload remains a concern in myelodysplastic syndrome (MDS) patients. Iron chelation therapy (ICT) thus plays an integral role in the management of these patients. Moreover, ICT has been shown to prolong leukemia free survival in MDS patients; however, the mechanisms responsible for this effect are unclear. Iron is a key molecule for regulating cytosolic aconitase 1 (ACO1) Additionally, the mutation of isocitrate dehydrogenase (IDH) the enzyme downstream of ACO1 in the TCA cycle, is associated with epigenetic abnormalities secondary to 2 hydroxyglutarate (2 HG) and DNA methylation. However, epigenetic abnormalities observed in many MDS patients occur without IDH mutation. We hypothesized that iron itself activates the ACO1 IDH pathway, which may increase 2 HG and DNA methylation, and eventually contribute to leukemogenesis without IDH mutation. Using whole RNA sequencing of bone marrow cells in iron overloaded mice, we observed that the enzymes, phosphoglucomutase 1, glycogen debranching enzyme, and isocitrate dehydrogenase 1 (Idh1) which are involved in glycogen and glucose metabolism, were increased. Digital PCR further showed that Idh1 and Aco1, enzymes involved in the TCA cycle, were also elevated. Additionally, enzymatic activities of TCA cycle and methylated DNA were increased. Iron chelation reversed these phenomena. In conclusion, iron activation of glucose metabolism causes an increase of 2 HG and DNA methylation.
Traditional Coping Strategies of Borana Pastoralists for Climate Extremes: A case of Yabello District, Borana Zone, Ethiopia

This study was undertaken in Yabello district of Borana zone to identify the ongoing coping strategi es of pastoralists in topical condition. The primary data collected from 123 sample households was analyzed using multi nomial logit model. The major coping strategies most common ly used in study area were Livestock diversification ba sed coping strategies, integrated crop livestock based diversification based coping strategies, livestock diversification, water and rangeland management bas ed coping strategies and Livestock diversification, inc ome earning opportunities and strategic feeding system based coping strategies. The multinomial logit model resul t indicated that sex of household head, education sta tus of household head, size of livestock holding, market d istance from homestead, access to credit, access to early w arning information, access to training and pastoral/agro pastoral income determines among coping strategies for clima te extremes. Generally, the pastorals' coping strategi es for climate extremes inclined to a multi choice coping strategies. Accordingly, establishment of formal early warning information, improving access to market, improving access to economic credit scheme, improving livestock ownersh ip and income of the household would enhance the pastoral capacity to the employ a multi choice coping strategies.
Fine grained sentiment analysis of social media with emotion sensing
Venue: 2016 Future Technologies Conference (FTC)

Social media is arguably the richest source of human generated text input. Opinions, feedbacks and critiques provided by internet users reflect attitudes and sentiments towards certain topics, products, or services. The sheer volume of such information makes it effectively impossible for any group of persons to read through. Thus, social media sentiment analysis has become an important area of work to make sense of the social media talk. However, most existing sentiment analysis techniques focus only on the aggregate level, classifying sentiments broadly into positive, neutral or negative, and lack the capabilities to perform fine grained sentiment analysis. This paper describes a social media analytics engine that employs a social adaptive fuzzy similarity based classification method to automatically classify text messages into sentiment categories (positive, negative, neutral and mixed) with the ability to identify their prevailing emotion categories (e.g. satisfaction, happiness, excitement, anger, sadness, and anxiety) It is also embedded within an end to end social media analysis system that has the capabilities to collect, filter, classify, and analyze social media text data and display a descriptive and predictive analytics dashboard for a given concept. The proposed method has been developed and is ready to be licensed to users.
A mobile visualization platform for exploring social media data

With the increasing application of using mobile device and social media, large amount of continuous information about human behaviors is available. Data visualization provides an insightful presentation for the large scale social media datasets. The focus of this paper is on the development of a mobile device based visualization and analysis platform for social media data for the purpose of retrieving and visualizing visitors' information for a specific region. This developed platform allows users to view the "big picture" of the visitors' locations information. The result shows that the developed platform 1) performs a satisfied data collection and data visualization on a mobile device, 2) assists users to understand the varieties of human behaviors while visiting a place, and 3) offers a feasible role in imaging immediate information from social media and leading to further policy making in related sectors and areas. Future research opportunities and challenges for social media data visualization are discussed. Social media, data visualization, mobile device
An energy efficient privacy preserving content sharing scheme in mobile social networks
Venue: Personal and Ubiquitous Computing

The rising popularity of mobile social media enables personalization of various content sharing and subscribing services. These two types of services entail serious privacy concerns not only to the confidentiality of shared content, but also to the privacy of end users such as their identities, interests and social relationships. Previous works established on the attribute based encryption (ABE) can provide fine grained access control of content. However, practical privacy preserving content sharing in mobile social networks either incurs great risk of information leaking to unauthorized third parties or suffers from high energy consumption for decrypting privacy preserving content. Motivated by these issues, this paper proposes a publish subscribe system with secure proxy decryption (PSSPD) in mobile social networks. First, an effective self contained privacy preserving access control method is introduced to protect the confidentiality of the content and the credentials of users. This method is based on ciphertext policy ABE and public key encryption with keyword search. After that, a secure proxy decryption mechanism is proposed to reduce the heavy burdens of energy consumption on performing ciphertext decryption at end users. The experimental results demonstrate the efficiency and privacy preservation effectiveness of PSSPD.
Relational and Masspersonal Maintenance: Romantic Partners' Use of Social Network Websites
Venue: 2016 49th Hawaii International Conference on System Sciences (HICSS)

As social network websites (SNSs) occupy the intersection of both interpersonal and mass media communication, the current research examined how public, private, and "masspersonal" features of SNSs affect relational maintenance between romantic couples. In Study 1, a survey of 309 Facebook users revealed that increases in dyadic public and private maintenance, and network maintenance communication were associated with greater feelings of presence and satisfaction. However, public and private dyadic maintenance had opposite relationships with partner uncertainty. To further examine these patterns, Study 2 employed an in depth content analysis of maintenance messages. Results from a sample of 94 Facebook users' maintenance messages indicated that selection of public and private SNS channels varied with respect to the valence and intimacy of the message.
Cyberbullying Detection with a Pronunciation Based Convolutional Neural Network
Venue: 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA)

Cyberbullying can have a deep and long lasting impact on its victims, who are often adolescents. Accurately detecting cyberbullying helps prevent it. However, the noise and errors in social media posts and messages make detecting cyberbullying very challenging. In this paper, we propose a novel pronunciation based convolutional neural network (PCNN) to address this challenge. Upon observing that the pronunciation of misspelled words in informal online conversations is often unchanged, we used the phoneme codes of the text as the features for a convolutional neural network. This procedure corrects spelling errors that did not alter the pronunciation, thereby alleviating the problem of noise and bullying data sparsity. To overcome class imbalance, a common problem in cyberbullying datasets, we implement three techniques that include threshold moving, cost function adjusting, and a hybrid solution in our model. We evaluate the performance of our models using two cyberbullying datasets collected from Twitter and Formspring.me. The results of our experiment show that PCNN can achieve improved recall and precision compared to baseline convolutional neural networks.
Speech Recognition Using Artificial Neural Network A Review

Speech is the most efficient mode of communication between peoples. This, being the best way of communication, could also be a useful interface to communicate with machines. Therefore the popularity of automatic speech recognition system has been greatly increased. There are different approaches to speech recognition like Hidden Markov Model (HMM) Dynamic Time Warping (DTW) Vector Quantization (VQ) etc. This paper provides a comprehensive study of use of Artificial Neural Networks (ANN) in speech recognition. The paper focuses on the different neural network related methods that can be used for speech recognition and compares their advantages and disadvantages. The conclusion is given on the most suitable method.  Networks, Training Algorithm, Speech Recognition, Artificial Intelligence, Feature Extraction, Pattern Recognition, LPC, MFCC, Perceptron, Feedforward Neural Networks, etc.
TAFSIR KEBENCIAN Studi Bias Gender dalam Tafsir Al Quran Karya Zaitunah Subhan

The paper objectives are to describe and to anlyze the Zainatunah Subhan view on the exegesis of gender verses in Al Quran. According to her, indeed there is gender bias if the verses are textually interpreted. Otherwise, Al Quran supports the equality of both verses, if the verses are interpreted contextually along with scientific explanation.
Detection of number of components in CANDECOMP/PARAFAC models via minimum description length
Venue: Digit. Signal Process.

Detecting the number of components of the CANDECOMP/PARAFAC (CP) model, also known as CP model order selection, is an essential task in signal processing and data mining applications. Existing multilinear detection algorithms for handling N dimensional data, where N 3 e.g. the CORe CONsistency DIAgnostic, rely on the CP decomposition which is computationally very expensive. An alternative solution is to rearrange the tensor as a matrix using the unfolding operation and then utilize the eigenvalues of the resultant matrices for CP model order selection. We propose to employ the eigenvalues associated with the unfolding along merged dimensions, namely, the multi mode eigenvalues, as well as the n mode eigenvalues for accurate rank detection. These multiple sets of eigenvalues are combined via the information theoretic criterion. By designing a sequential detection scheme starting from the most squared unfolded matrix, the identifiable rank is increased to the square root of the product of all dimension lengths, which renders the detection algorithm to estimate the rank that can exceed any individual dimension length. The conditions under which the proposed multilinear detection algorithm correctly detects the tensor rank are theoretically investigated and its computational efficiency and detection performance are verified. The problem of CANDECOMP/PARAFAC (CP) model order selection is addressed.Computational efficiency is achieved via matricization of a tensor.Eigenvalues associated with the block or multi mode matricization are exploited.Able to detect rank up to the square root of the product of all dimension lengths.Accuracy comparable to CP decomposition based tensor rank detectors.
Product design and business model strategies for a circular economy

The transition within business from a linear to a circular economy brings with it a range of practical challenges for companies. The following question is addressed: What are the product design and business model strategies for companies that want to move to a circular economy model? This paper develops a framework of strategies to guide designers and business strategists in the move from a linear to a circular economy. Building on Stahel, the terminology of slowing, closing, and narrowing resource loops is introduced. A list of product design strategies, business model strategies, and examples for key decision makers in businesses is introduced, to facilitate the move to a circular economy. This framework also opens up a future research agenda for the circular economy.
The Effects of Early Childhood Teacher's Self differentiation and Self efficacy on Psychological Well being

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A flexible technique based on fundamental matrix for camera self calibration with variable intrinsic parameters from two views
Venue: J. Vis. Commun. Image Represent.

Self calibrate cameras with varying focal length.Automatic estimation of the intrinsic parameters of the camera.Works freely in the domain of self calibration without any prior knowledge about the scene or on the cameras. We propose a new self calibration technique for cameras with varying intrinsic parameters that can be computed using only information contained in the images themselves. The method does not need any a priori knowledge on the orientations of the camera and is based on the use of a 3 D scene containing an unknown isosceles right triangle. The importance of our approach resides at minimizing constraints on the self calibration system and the use of only two images to estimate these parameters. This method is based on the formulation of a nonlinear cost function from the relationship between two matches which are the projection of two points representing vertices of an isosceles right triangle, and the relationship between the images of the absolute conic. The resolution of this function enables us to estimate the cameras intrinsic parameters. The algorithm is implemented and validated on several sets of synthetic and real image data.
Cross ratio based line scan camera calibration using a planar pattern

A flexible new technique is proposed to calibrate the geometric model of line scan cameras. In this technique, the line scan camera is rigidly coupled to a calibrated frame camera to establish a pair of stereo cameras. The linear displacements and rotation angles between the two cameras are fixed but unknown. This technique only requires the pair of stereo cameras to observe a specially designed planar pattern shown at a few (at least two) different orientations. At each orientation, a stereo pair is obtained including a linear array image and a frame image. Radial distortion of the line scan camera is modeled. The calibration scheme includes two stages. First, point correspondences are established from the pattern geometry and the projective invariance of cross ratio. Second, with a two step calibration procedure, the intrinsic parameters of the line scan camera are recovered from several stereo pairs together with the rigid transform parameters between the pair of stereo cameras. Both computer simulation and real data experiments are conducted to test the precision and robustness of the calibration algorithm, and very good calibration results have been obtained. Compared with classical techniques which use three dimensional calibration objects or controllable moving platforms, our technique is affordable and flexible in close range photogrammetric applications.