nils-herrmann/clean_scirepeval huggingface dataset:
From macro- to microplastics - Analysis of EU regulation along the life cycle of plastic bags.

Plastic pollution and its environmental effects has received global attention the recent years. However, limited attention has so far been directed towards how plastics are regulated in a life cycle perspective and how regulatory gaps can be addressed in order to limit and prevent environmental exposure and hazards of macro- and microplastics. In this paper, we map European regulation taking outset in the life cycle perspective of plastic carrier bags: from plastic bag production to when it enters the environment. Relevant regulatory frameworks, directives and authorities along the life cycle are identified and their role in regulation of plastics is discussed. Most important regulations were identified as: the EU chemical Regulation, the Packaging and Packaging Waste Directive including the amending Directive regarding regulation of the consumption of lightweight plastic carrier bags, the Waste Framework Directive and the Directive on the Landfill of Waste. The main gaps identified relate to lack of clear definitions of categories of polymers, unambitious recycling rates and lack of consideration of macro- and microplastics in key pieces of legislation. We recommend that polymers are categorized according to whether they are polymers with the same monomer constituents (homopolymers) or with different monomer constituents (copolymers) and that polymers are no longer exempt from registration and evaluation under REACH. Plastics should furthermore have the same high level of monitoring and reporting requirements as hazardous waste involving stricter requirements to labelling, recordkeeping, monitoring and control over the whole lifecycle. Finally, we recommend that more ambitious recycle and recovery targets are set across the EU. Regulation of the consumption of lightweight plastic carrier bags should also apply to heavyweight plastic carrier bags. Last, the Marine and Water Framework Directives should specifically address plastic waste affecting water quality.
Nearly Optimal Distributed Algorithm for Computing Betweenness Centrality

In this paper, we propose an O(N) time distributed algorithm for computing betweenness centralities of all nodes in the network where N is the number of nodes. Our distributed algorithm is designed under the widely employed CONGEST model in the distributed computing community which limits each message only contains O(log N) bits. To our best knowledge, this is the first linear time deterministic distributed algorithm for computing the betweenness centralities in the published literature. We also give a lower bound for distributively computing the betweenness centrality under the CONGEST model as Ω(D+N/ log N) where D is the diameter of the network. This implies that our distributed algorithm is nearly optimal.
AN INTRODUCTION TO DIMENSION THEORY AND FRACTAL GEOMETRY : FRACTAL DIMENSIONS AND MEASURES

“When we say that space has the dimensions three, what do we mean? If to divide a continuum C it suffices to consider as cuts a certain number of distinguishable points, we say that this continuum is of dimension one. If, on the contrary, to divide a continuum it suffices to use cuts which form one or several continua of dimension one, then we say that C is a continuum of dimension two. If cuts which form one or several continua of at most dimension two suffice, we say that C is a continuum of dimension three; and so on.”
See what's enBlogue: real-time emergent topic identification in social media

With the increasing popularity of Web 2.0 streams, people become overwhelmed by the available information. This is partly countered by tagging blog posts and tweets, so that users can filter messages according to their tags. However, this is insufficient for detecting newly emerging topics that are not reflected by a single tag but are rather expressed by unusual tag combinations. This paper presents enBlogue, an approach for automatically detecting such emergent topics. EnBlogue uses a time-sliding window to compute statistics about tags and tag-pairs. These statistics are then used to identify unusual shifts in correlations, most of the time caused by real-world events. We analyze the strength of these shifts and measure the degree of unpredictability they include, used to rank tag-pairs expressing emergent topics. Additionally, this "indicator of surprise" is carried over to subsequent time points, as user interests do not abruptly vanish from one moment to the other. To avoid monitoring all tag-pairs we can also select a subset of tags, e. g., the most popular or volatile of them, to be used as seed-tags for subsequent pair-wise correlation computations. The system is fully implemented and publicly available on the Web, processing live Twitter data. We present experimental studies based on real world datasets demonstrating both the prediction quality by means of a user study and the efficiency of enBlogue.
World Heart Federation criteria for echocardiographic diagnosis of rheumatic heart disease—an evidence-based guideline

Over the past 5 years, the advent of echocardiographic screening for rheumatic heart disease (RHD) has revealed a higher RHD burden than previously thought. In light of this global experience, the development of new international echocardiographic guidelines that address the full spectrum of the rheumatic disease process is opportune. Systematic differences in the reporting of and diagnostic approach to RHD exist, reflecting differences in local experience and disease patterns. The World Heart Federation echocardiographic criteria for RHD have, therefore, been developed and are formulated on the basis of the best available evidence. Three categories are defined on the basis of assessment by 2D, continuous-wave, and color-Doppler echocardiography: 'definite RHD', 'borderline RHD', and 'normal'. Four subcategories of 'definite RHD' and three subcategories of 'borderline RHD' exist, to reflect the various disease patterns. The morphological features of RHD and the criteria for pathological mitral and aortic regurgitation are also defined. The criteria are modified for those aged over 20 years on the basis of the available evidence. The standardized criteria aim to permit rapid and consistent identification of individuals with RHD without a clear history of acute rheumatic fever and hence allow enrollment into secondary prophylaxis programs. However, important unanswered questions remain about the importance of subclinical disease (borderline or definite RHD on echocardiography without a clinical pathological murmur), and about the practicalities of implementing screening programs. These standardized criteria will help enable new studies to be designed to evaluate the role of echocardiographic screening in RHD control.
Bioinformatics tools for cancer metabolomics

It is well known that significant metabolic change take place as cells are transformed from normal to malignant. This review focuses on the use of different bioinformatics tools in cancer metabolomics studies. The article begins by describing different metabolomics technologies and data generation techniques. Overview of the data pre-processing techniques is provided and multivariate data analysis techniques are discussed and illustrated with case studies, including principal component analysis, clustering techniques, self-organizing maps, partial least squares, and discriminant function analysis. Also included is a discussion of available software packages.
Detecting Profile Injection Attacks in Collaborative Recommender Systems

Collaborative recommender systems are known to be highly vulnerable to profile injection attacks, attacks that involve the insertion of biased profiles into the ratings database for the purpose of altering the system's recommendation behavior. In prior work, we and others have identified a number of models for such attacks and shown their effectiveness. This paper describes a classification approach to the problem of detecting and responding to profile injection attacks. This technique significantly reduces the effectiveness of the most powerful attack models previously studied
Mr . Risk ! Please Trust Me : Trust Antecedents that Increase Online Consumer Purchase Intention

With the rapid growth of e-commerce, the B2C of e-commerce has been a significant issue. The purpose of this study aims to predict consumers’ purchase intentions by integrating trust and perceived risk into the model to empirically examine the impact of key variables. 705 samples were obtained from online users purchasing from e-vendor of Yahoo! Kimo. This study applied the Structural Equation Model to examine consumers’ online shopping based on the Technology Acceptance Model (TAM). The results indicate that perceived ease of use (PEOU), perceived usefulness (PU), trust, and perceived risk significantly impact purchase intentions both directly and indirectly. Moreover, trust significantly reduced online consumer perceived risk during online shopping. This study provides evidence of the relationship between consumers’ purchase intention, perceived trust and perceived risk to websites of specific e-vendors. Such knowledge may help to inform promotion, designing, and advertising website strategies employed by practitioners.
A local planner for Ackermann-driven vehicles in ROS SBPL

For a mobile service robot, safe navigation is essential. To do so, the robot needs to be equipped with collision avoidance and global path planning capabilities. The target platforms considered in this paper are Ackermann-driven vehicles. Hence, a planning approach which directly takes the kinematic and dynamic constraints of the vehicle into account is required. The Search-based Planning Library (SBPL) package of the Robot Operating System (ROS) provides global path planning which takes these constraints into account. However, it misses a local planner that can also make use of the Ackermann kinematic constraints for collision avoidance. A local planner is useful to take dynamic obstacles into account as early as possible. In this paper, we extend the SBPL included in ROS by a local planner, which makes use of motion primitives. We extend the ROS package and show first experimental results on Ackermann-driven vehicles.
Design of Virtual Oscilloscope Based LabVIEW

The virtual instrument is the main content of instrument technology nowadays. This article details the implementation process of the virtual oscilloscope. It is designed by LabVIEW graphical programming language. The virtual oscilloscope can achieve waveform display, channel selection, data collection, data reading, writing and storage, spectrum analysis, printing and waveform parameters measurement. It also has a friendly user interface and can be operated conveniently.
Implications of Internet architecture on net neutrality

Net neutrality represents the idea that Internet users are entitled to service that does not discriminate on the basis of source, destination, or ownership of Internet traffic. The United States Congress is considering legislation on net neutrality, and debate over the issue has generated intense lobbying. Congressional action will substantially affect the evolution of the Internet and of future Internet research. In this article, we argue that neither the pro nor anti net neutrality positions are consistent with the philosophy of Internet architecture. We develop a net neutrality policy founded on a segmentation of Internet services into infrastructure services and application services, based on the Internet's layered architecture. Our net neutrality policy restricts an Internet service Provider's ability to engage in anticompetitive behavior while simultaneously ensuring that it can use desirable forms of network management. We illustrate the effect of this policy by discussing acceptable and unacceptable uses of network management.
The effects of balance and postural stability exercises on spa based rehabilitation programme in patients with ankylosing spondylitis.

Ankylosing spondylitis (AS) can cause severe functional disorders that lead to loss of balance.



The aim of this study was to investigate the effects of balance and postural stability exercises on spa based rehabilitation programme in AS subjects.



Twenty-one participants were randomized to the study (n= 11) and control groups (n= 10). Patients balance and stability were assessed with the Berg Balance Scale (BBS), Timed Up and Go (TUG) Test, Single Leg Stance Test (SLST) and Functional Reach Test (FRT). AS spesicied measures were used for assessing to other parameters. The treatment plan for both groups consisted of conventional transcutaneous electrical nerve stimulation (TENS), spa and land-based exercises 5 days per week for 3 weeks. The study group performed exercises based on postural stability and balance with routine physiotherapy practice in thermal water and in exercise room.



The TUG, SLST and FUT scores were significantly increased in the study group. In both groups, the BASMI, BASFI, BASDAI and ASQoL scores decreased significantly by the end of the treatment period (p< 0.05).



In AS rehabilitation, performing balance and stability exercises in addition to spa based routine approaches can increase the duration of maintaining balance and can improve the benefits of physiotherapy.
A hybrid KMV model, random forests and rough set theory approach for credit rating

In current credit ratings models, various accounting-based information are usually selected as prediction variables, based on historical information rather than the market’s assessment for future. In the study, we propose credit rating prediction model using market-based information as a predictive variable. In the proposed method, Moody’s KMV (KMV) is employed as a tool to evaluate the market-based information of each corporation. To verify the proposed method, using the hybrid model, which combine random forests (RF) and rough set theory (RST) to extract useful information for credit rating. The results show that market-based information does provide valuable information in credit rating predictions. Moreover, the proposed approach provides better classification results and generates meaningful rules for credit ratings.
A structure for children-oriented Human Computer Interaction

To improve the existing techniques of Human Computer Interaction (HCI) for children, some principles for HCI design are proposed based on children's psychological and physiological characteristics. Then a HCI structure WisPad is presented for children according to the principles. WisPad incorporates tangible user interface, gesture interaction, Avatar-based HCI, high-level semantics interactive technology and realizes the natural interaction between children and computers.
Distance measures for layout-based document image retrieval

Most methods for document image retrieval rely solely on text information to find similar documents. This paper describes a way to use layout information for document image retrieval instead. A new class of distance measures is introduced for documents with Manhattan layouts, based on a two-step procedure: First, the distances between the blocks of two layouts are calculated. Then, the blocks of one layout are assigned to the blocks of the other layout in a matching step. Different block distances and matching methods are compared and evaluated using the publicly available MARG database. On this dataset, the layout type can be determined successfully in 92.6% of the cases using the best distance measure in a nearest neighbor classifier. The experiments show that the best distance measure for this task is the overlapping area combined with the Manhattan distance of the corner points as block distance together with the minimum weight edge cover matching
A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms and Software

This paper describes the discipline of distance metric learning, a branch of machine learning that aims to learn distances from the data. Distance metric learning can be useful to improve similarity learning algorithms, and also has applications in dimensionality reduction. We describe the distance metric learning problem and analyze its main mathematical foundations. We discuss some of the most popular distance metric learning techniques used in classification, showing their goals and the required information to understand and use them. Furthermore, we present a Python package that collects a set of 17 distance metric learning techniques explained in this paper, with some experiments to evaluate the performance of the different algorithms. Finally, we discuss several possibilities of future work in this topic.
Remembering history with convolutional LSTM for anomaly detection

This paper tackles anomaly detection in videos, which is an extremely challenging task because anomaly is unbounded. We approach this task by leveraging a Convolutional Neural Network (CNN or ConvNet) for appearance encoding for each frame, and leveraging a Convolutional Long Short Term Memory (ConvLSTM) for memorizing all past frames which corresponds to the motion information. Then we integrate ConvNet and ConvLSTM with Auto-Encoder, which is referred to as ConvLSTM-AE, to learn the regularity of appearance and motion for the ordinary moments. Compared with 3D Convolutional Auto-Encoder based anomaly detection, our main contribution lies in that we propose a ConvLSTM-AE framework which better encodes the change of appearance and motion for normal events, respectively. To evaluate our method, we first conduct experiments on a synthesized Moving-MNIST dataset under controlled settings, and results show that our method can easily identify the change of appearance and motion. Extensive experiments on real anomaly datasets further validate the effectiveness of our method for anomaly detection.
Corrosion of silicon integrated circuits and lifetime predictions in implantable electronic devices.

Corrosion is a prime concern for active implantable devices. In this paper we review the principles underlying the concepts of hermetic packages and encapsulation, used to protect implanted electronics, some of which remain widely overlooked. We discuss how technological advances have created a need to update the way we evaluate the suitability of both protection methods. We demonstrate how lifetime predictability is lost for very small hermetic packages and introduce a single parameter to compare different packages, with an equation to calculate the minimum sensitivity required from a test method to guarantee a given lifetime. In the second part of this paper, we review the literature on the corrosion of encapsulated integrated circuits (ICs) and, following a new analysis of published data, we propose an equation for the pre-corrosion lifetime of implanted ICs, and discuss the influence of the temperature, relative humidity, encapsulation and field-strength. As any new protection will be tested under accelerated conditions, we demonstrate the sensitivity of acceleration factors to some inaccurately known parameters. These results are relevant for any application of electronics working in a moist environment. Our comparison of encapsulation and hermetic packages suggests that both concepts may be suitable for future implants.
Spring 6-10-2017 ANTECEDENTS OF EMPLOYEES ' INFORMATION SECURITY AWARENESS-REVIEW , SYNTHESIS , AND DIRECTIONS FOR FUTURE RESEARCH

Living in a digital age, where all kinds of information are accessible electronically at all times, organizations worldwide struggle to keep their information assets secure. Interestingly, the majority of organizational information systems security (ISS) incidents are the direct or indirect result of human errors. To explore how organizations can defend themselves against harmful ISS behaviour, employees’ information security awareness (ISA) has become a top-priority in research and practice. ISA is referred to as a state of consciousness and knowledge about security issues and is a strong predictor of security compliant behaviour. However, to date knowledge about the factors that are responsible for some employees having a higher level of ISA than others is limited and widely dispersed among multidisciplinary outlets. Therefore, our study provides an extensive review of the literature on ISA’s antecedents with the aim to synthesize the literature and to reveal areas for further research. We analysed 44 publications to discern various institutional, individual, and socio-environmental ISA antecedents. Identifying and understanding these factors will be useful for stakeholders interested in improving the effectiveness of awareness strategies, in increasing employees’ ISA and in ultimately lowering the substantial ISS threats for organizations and society.
The misuse of the NASA metrics data program data sets for automated software defect prediction

The NASA Metrics Data Program data sets have been heavily used in software defect prediction experiments.  To demonstrate and explain why these data sets require significant pre-processing in order to be suitable for defect prediction.  A meticulously documented data cleansing process involving all 13 of the original NASA data sets.  Post our novel data cleansing process; each of the data sets had between 6 to 90 percent less of their original number of recorded values.  One: Researchers need to analyse the data that forms the basis of their findings in the context of how it will be used.  Defect prediction data sets could benefit from lower level code metrics in addition to those more commonly used, as these will help to distinguish modules, reducing the likelihood of repeated data points.  The bulk of defect prediction experiments based on the NASA Metrics Data Program data sets may have led to erroneous findings. This is mainly due to repeated data points potentially causing substantial amounts of training and testing data to be identical.
A conceptual framework of e-fraud control in an integrated supply chain

The integration of supply chains offers many benefits; yet, it may also render organisations more vulnerable to electronic fraud (e-fraud). E-fraud can drain on organisations’ financial resources, and can have a significant adverse effect on the ability to achieve their strategic objectives. Therefore, efraud control should be part of corporate board-level due diligence, and should be integrated into organisations’ practices and business plans. Management is responsible for taking into consideration the relevant cultural, strategic and implementation elements that inter-relate with each other and to coordinating the human, technological and financial resources necessary to designing and implementing policies and procedures for controlling e-fraud. Due to the characteristics of integrated supply chains, a move from the traditional vertical approach to a systemic, horizontal-vertical approach is necessary. Although the e-fraud risk cannot be eliminated, risk mitigation policies and processes tailored to an organisation’s particular vulnerabilities can significantly reduce the risk and may even preclude certain classes of frauds. In this paper, a conceptual framework of e-fraud control in an integrated supply chain is proposed. The proposed conceptual framework can help managers and practitioners better understand the issues and plan the activities involved in a systemic, horizontal-vertical approach to e-fraud control in an integrated supply chain, and can be a basis upon which empirical studies can be build.