nils-herrmann/clean_scirepeval huggingface dataset:
Automatically Generating Extraction Patterns from Untagged Text

Many corpus-based natural language processing systems rely on text corpora that have been manually annotated with syntactic or semantic tags. In particular, all previous dictionary construction systems for information extraction have used an annotated training corpus or some form of annotated input. We have developed a system called AutoSlog-TS that creates dictionaries of extraction patterns using only untagged text. AutoSlog-TS is based on the AutoSlog system, which generated extraction patterns using annotated text and a set of heuristic rules. By adapting AutoSlog and combining it with statistical techniques, we eliminated its dependency on tagged text. In experiments with the MUG-4 terrorism domain, AutoSlogTS created a dictionary of extraction patterns that performed comparably to a dictionary created by AutoSlog, using only preclassified texts as input.
Gestational diabetes mellitus.

Gestational diabetes mellitus (GDM) is defined as glucose intolerance of various degrees that is first detected during pregnancy. GDM is detected through the screening of pregnant women for clinical risk factors and, among at-risk women, testing for abnormal glucose tolerance that is usually, but not invariably, mild and asymptomatic. GDM appears to result from the same broad spectrum of physiological and genetic abnormalities that characterize diabetes outside of pregnancy. Indeed, women with GDM are at high risk for having or developing diabetes when they are not pregnant. Thus, GDM provides a unique opportunity to study the early pathogenesis of diabetes and to develop interventions to prevent the disease.
Predicting personality with social behavior: a comparative study

In this paper, we study the problem of predicting personality with features based on social behavior. While network position and text analysis are often used in personality prediction, the use of social behavior is fairly new. Often studies of social behavior either concentrate on a single behavior or trait, or simply use behavior to predict ties that are then used in analysis of network position. To study this problem, we introduce novel features based on a person’s social actions in general, towards specific individuals in particular. We also compute the variation of these actions among all the social contacts of a person as well as the actions of friends. We show that social behavior alone, without the help of any textual or network position information, provides a good basis for personality prediction. We then provide a unique comparative study that finds the most significant features based on social behavior in predicting personality for three different communication mediums: Twitter, SMS and phone calls. These mediums offer us with social behavior from public and private contexts, containing messaging and voice call type exchanges. We find behaviors that are distinctive and normative among the ones we study. We also illustrate how behavioral features relate to different personality traits. We also show the various similarities and differences between different mediums in terms of social behavior. Note that all behavioral features are based on statistical properties of the number and the time of social actions and do not consider the textual content. As a result, they can be applied in many different settings. Furthermore, our findings show us how behavioral features can be customized to a specific medium and personality trait.
An interactive tool for manual, semi-automatic and automatic video annotation

The annotation of image and video data of large datasets is a fundamental task in multimedia information retrieval and computer vision applications. The aim of annotation tools is to relieve the user from the burden of the manual annotation as much as possible. To achieve this ideal goal, many different functionalities are required in order to make the annotations process as automatic as possible. Motivated by the limitations of existing tools, we have developed the iVAT: an interactive Video Annotation Tool. It supports manual, semi-automatic and automatic annotations through the interaction of the user with various detection algorithms. To the best of our knowledge, it is the first tool that integrates several computer vision algorithms working in an interactive and incremental learning framework. This makes the tool flexible and suitable to be used in different application domains. A quantitative and qualitative evaluation of the proposed tool on a challenging case study domain is presented and discussed. Results demonstrate that the use of the semi-automatic, as well as the automatic, modality drastically reduces the human effort while preserving the quality of the annotations.
Game theory and human evolution: a critique of some recent interpretations of experimental games.

Economists and psychologists have been testing Nash equilibrium predictions of game theory models of human behavior. In many instances, humans do not conform to the predictions. These results are of great interest to biologists because they also raise questions about well-known ESS models of cooperation. Cooperation in certain one-shot, anonymous interactions, and a willingness to punish others at a net cost to oneself are some of the most intriguing deviations from standard theory. One proposed explanation for these results that is receiving increasing attention invokes the cultural group selection of 'other regarding' social norms. We critically review this explanation. We conclude that experimental results reveal limits in two implicit models of cognitive structure commonly employed by economists and evolutionary biologists.
Tuning Response Curves for Synthetic Biology

Synthetic biology may be viewed as an effort to establish, formalize, and develop an engineering discipline in the context of biological systems. The ability to tune the properties of individual components is central to the process of system design in all fields of engineering, and synthetic biology is no exception. A large and growing number of approaches have been developed for tuning the responses of cellular systems, and here we address specifically the issue of tuning the rate of response of a system: given a system where an input affects the rate of change of an output, how can the shape of the response curve be altered experimentally? This affects a system's dynamics as well as its steady-state properties, both of which are critical in the design of systems in synthetic biology, particularly those with multiple components. We begin by reviewing a mathematical formulation that captures a broad class of biological response curves and use this to define a standard set of varieties of tuning: vertical shifting, horizontal scaling, and the like. We then survey the experimental literature, classifying the results into our defined categories, and organizing them by regulatory level: transcriptional, post-transcriptional, and post-translational.
Enhanced Operating System Security Through Efficient and Fine-grained Address Space Randomization

In recent years, the deployment of many applicationlevel countermeasures against memory errors and the increasing number of vulnerabilities discovered in the kernel has fostered a renewed interest in kernel-level exploitation. Unfortunately, no comprehensive and wellestablished mechanism exists to protect the operating system from arbitrary attacks, due to the relatively new development of the area and the challenges involved. In this paper, we propose the first design for finegrained address space randomization (ASR) inside the operating system (OS), providing an efficient and comprehensive countermeasure against classic and emerging attacks, such as return-oriented programming. To motivate our design, we investigate the differences with application-level ASR and find that some of the wellestablished assumptions in existing solutions are no longer valid inside the OS; above all, perhaps, that information leakage becomes a major concern in the new context. We show that our ASR strategy outperforms stateof-the-art solutions in terms of both performance and security without affecting the software distribution model. Finally, we present the first comprehensive live rerandomization strategy, which we found to be particularly important inside the OS. Experimental results demonstrate that our techniques yield low run-time performance overhead (less than 5% on average on both SPEC and syscall-intensive benchmarks) and limited run-time memory footprint increase (around 15% during the execution of our benchmarks). We believe our techniques can greatly enhance the level of OS security without compromising the performance and reliability of the OS.
Environmental implications of plastic debris in marine settings--entanglement, ingestion, smothering, hangers-on, hitch-hiking and alien invasions.

Over the past five or six decades, contamination and pollution of the world's enclosed seas, coastal waters and the wider open oceans by plastics and other synthetic, non-biodegradable materials (generally known as 'marine debris') has been an ever-increasing phenomenon. The sources of these polluting materials are both land- and marine-based, their origins may be local or distant, and the environmental consequences are many and varied. The more widely recognized problems are typically associated with entanglement, ingestion, suffocation and general debilitation, and are often related to stranding events and public perception. Among the less frequently recognized and recorded problems are global hazards to shipping, fisheries and other maritime activities. Today, there are rapidly developing research interests in the biota attracted to freely floating (i.e. pelagic) marine debris, commonly known as 'hangers-on and hitch-hikers' as well as material sinking to the sea floor despite being buoyant. Dispersal of aggressive alien and invasive species by these mechanisms leads one to reflect on the possibilities that ensuing invasions could endanger sensitive, or at-risk coastal environments (both marine and terrestrial) far from their native habitats.
A Review of Non-Invasive Sensory Feedback Methods for Transradial Prosthetic Hands

Any implant or prosthesis replacing a function or functions of an organ or group of organs should be biologically and sensorily integrated with the human body in order to increase their acceptance with their user. If this replacement is for a human hand, which is an important interface between humans and their environment, the acceptance issue and developing sensory-motor embodiment will be more challenging. Despite progress in prosthesis technologies, 50–60% of hand amputees wear a prosthetic device. One primary reason for the rejection of the prosthetic hands is that there is no or negligibly small feedback or tactile sensation from the hand to the user, making the hands less functional. In fact, the loss of a hand means interrupting the closed-loop sensory feedback between the brain (motor control) and the hand (sensory feedback through the nerves). The lack of feedback requires significant cognitive efforts from the user in order to do basic gestures and daily activities. To this aim, recently, there has been significant development in the provision of sensory feedback from transradial prosthetic hands, to enable the user take part in the control loop and improve user embodiment. Sensory feedback to the hand users can be provided via invasive and non-invasive methods. The latter includes the use of temperature, vibration, mechanical pressure and skin stretching, electrotactile stimulation, phantom limb stimulation, audio feedback, and augmented reality. This paper provides a comprehensive review of the non-invasive methods, performs their critical evaluation, and presents challenges and opportunities associated with the non-invasive sensory feedback methods.
The role played by the concept of presence in validating the efficacy of a cybertherapy treatment: a literature review

The present paper considers the existing research in cybertherapy, which is a psychological therapy carried out with the use of a mediated environment, and examines the way in which the users’ sense of presence in the mediated environment can be of relevance for the validation of the intervention. With this purpose, a collection of 41 papers reporting the measurement of presence in the context of a cybertherapy treatment has been identified and examined. The general relevance of presence in cybertherapy and the measurement techniques adopted in the studies collected here are described and discussed. The way in which presence corresponds to establishing internal validity, convergent or predictive validity and external validity of a treatment is examined. In conclusion, a checklist to apply when planning a validation study is proposed, to improve the way in which presence is used.
Monitoring the Application-Layer DDoS Attacks for Popular Websites

Distributed denial of service (DDoS) attack is a continuous critical threat to the Internet. Derived from the low layers, new application-layer-based DDoS attacks utilizing legitimate HTTP requests to overwhelm victim resources are more undetectable. The case may be more serious when such attacks mimic or occur during the flash crowd event of a popular Website. Focusing on the detection for such new DDoS attacks, a scheme based on document popularity is introduced. An Access Matrix is defined to capture the spatial-temporal patterns of a normal flash crowd. Principal component analysis and independent component analysis are applied to abstract the multidimensional Access Matrix. A novel anomaly detector based on hidden semi-Markov model is proposed to describe the dynamics of Access Matrix and to detect the attacks. The entropy of document popularity fitting to the model is used to detect the potential application-layer DDoS attacks. Numerical results based on real Web traffic data are presented to demonstrate the effectiveness of the proposed method.
Face Detection By Finding The Facial Features And The Angle of Inclination of Tilted Face

Face is a popular topic of research in computer vision, image analysis and understanding. This paper proposes a method to detect straight posed face as well as tilted face in colour images. Algorithm first detects skin colour region and then skin region is further processed by finding connected components and holes. Each connected components is tested to extract facial features and Y-value of each holes. If features exist in the connected component then the component is concluded as face. The Y-value of both eyes are compared to find whether the face is straight or tilted. For tilted face, the angle of tilt is determined and the input image is rotated by the angle of tilt to straighten up the face. After straightening the face, the rectangle is drawn to enclose the face. The dimension of drawn rectangle is obtained by using the distance parameter of the line between two eyes.
Evidence-based practice: functional rhinoplasty.

The cause of nasal obstruction can often be attributed to pathologic conditions of the nasal valve. The key physical examination finding in nasal valve compromise is inspiratory collapse of the nasal sidewall. Validated subjective and objective measures evaluating nasal obstruction exist, although with weak correlation. Functional rhinoplasty encompasses the surgical techniques used to address obstruction occurring in this area. These techniques aim to increase the size of the nasal valve opening and/or strengthen the lateral nasal wall and nasal ala, preventing dynamic collapse. Much of the supporting evidence for functional rhinoplasty consists of observational studies that are universally favorable.
WG-8: A Lightweight Stream Cipher for Resource-Constrained Smart Devices

Lightweight cryptographic primitives are essential for securing pervasive embedded devices like RFID tags, smart cards, and wireless sensor nodes. In this paper, we present a lightweight stream cipher WG-8, which is tailored from the well-known Welch-Gong (WG) stream cipher family, for resource-constrained devices. WG-8 inherits the good randomness and cryptographic properties of the WG stream cipher family and is resistant to the most common attacks against stream ciphers. The software implementations of the WG-8 stream cipher on two popular lowpower microcontrollers as well as the extensive comparison with other lightweight cryptography implementations highlight that in the context of securing lightweight embedded applications WG-8 has favorable performance and low energy consumption.
Desalination by ammonia – carbon dioxide forward osmosis : Influence of draw and feed solution concentrations on process performance

Forward (direct) osmosis (FO) using semi-permeable polymeric membranes may be a viable alternative to reverse osmosis as a lower cost and more environmentally friendly desalination technology. The driving force in the described FO process is provided by a draw solution comprising highly soluble gases—ammonia and carbon dioxide. Using a commercially available FO membrane, experiments conducted in a crossflow, flatsheet membrane filtration cell yielded water fluxes ranging from 1 to 10 m/s (2.1 to 21.2 gal ft−2 d−1 or 3.6 to 36.0 l m−2 h−1) for a wide range of draw and feed solution concentrations. It was found, however, that the experimental water fluxes were far lower than those anticipated based on a t a t s
Intellectual capital disclosure in Malaysia

This study investigates intellectual capital (IC) disclosure in Malaysian public listed companies. Specifically, this research examines the relationship between IC disclosure and companies' profitability, productivity, and firm size. We measure the IC disclosure using the IC disclosure index and I C disclosure frequency. The sample includes 255 firm-year observations from 2006-2008. The results from our content analysis confirm those of prior research that the IC disclosure has been increasing over time. The study finds that human capital is the most reported intellectual capital disclosure. In addition, we also find that firm size positively contribute to the disclosure of IC. The result of this study added to the body of literature by providing evidence on the relationship between IC disclosure and firms' characteristics.
The activation of attentional networks

Alerting, orienting, and executive control are widely thought to be relatively independent aspects of attention that are linked to separable brain regions. However, neuroimaging studies have yet to examine evidence for the anatomical separability of these three aspects of attention in the same subjects performing the same task. The attention network test (ANT) examines the effects of cues and targets within a single reaction time task to provide a means of exploring the efficiency of the alerting, orienting, and executive control networks involved in attention. It also provides an opportunity to examine the brain activity of these three networks as they operate in a single integrated task. We used event-related functional magnetic resonance imaging (fMRI) to explore the brain areas involved in the three attention systems targeted by the ANT. The alerting contrast showed strong thalamic involvement and activation of anterior and posterior cortical sites. As expected, the orienting contrast activated parietal sites and frontal eye fields. The executive control network contrast showed activation of the anterior cingulate along with several other brain areas. With some exceptions, activation patterns of these three networks within this single task are consistent with previous fMRI studies that have been studied in separate tasks. Overall, the fMRI results suggest that the functional contrasts within this single task differentially activate three separable anatomical networks related to the components of attention.
Secure Cloud Container: Runtime Behavior Monitoring Using Most Privileged Container (MPC)

Hypervisor-based virtualization rapidly becomes a commodity, and it turns valuable in many scenarios such as resource optimization, uptime maximization, and consolidation. Container-based application virtualization is an appropriate solution to develop a light weighted partitioning by providing application isolation with less overhead. Undoubtedly, container based virtualization delivers a lightweight and efficient environment, however raises some security concerns as it allows isolated processes to utilize an underlying host kernel. A new security layer with the Most Privileged Container (MPC) is proposed in this article. The proposed MPC layer exhibits three main functional blocks: Access policies, Black list database, and Runtime monitoring. The introduced MPC layer implements privilege based access control and assigns resource access permissions based on policies and the security profiles of containerized application user processes. Furthermore, the monitoring block examines the runtime behavior of containers and black list database is updated if the container violets its policies. The proposed MPC layer provides higher level of application container security against potential threats.
BotCensor: Detecting DGA-Based Botnet Using Two-Stage Anomaly Detection

Nowadays, most botnets utilize domain generation algorithms (DGAs) to build resilient and agile command and control (C&C) channels. Specifically, botmasters employ DGAs to dynamically produce a large number of random domains and only register a small subset for their actual C&C servers with the purpose to defend them from takeovers and blacklisting attempts. While many approaches and models have been developed to detect DGA-based botnets, they suffer from several limitations, such as difficulties of DNS traffic collection, low feasibility and scalability, and so forth. In this paper, we present BotCensor, a new system that can determine if a host is infected with certain DGA malware with two-stage anomaly detection. In the first stage, we preliminarily attempt to identify malicious domains using a Markov model, and in the second stage, we re-examine the hosts that requested aforementioned malicious domains using novelty detection algorithms. Our experimental results show that our approach performs very well on identifying previously unknown DGA-generated domains and detects DGA bots with high efficiency and efficacy. Our approach not only can be regarded as security forensics tools, but also can be used to prevent malware infections and spread.
Scaling Agile Development in Mechatronic Organizations - A Comparative Case Study

Agile software development principles enable companies to successfully and quickly deliver software by meeting their customers' expectations while focusing on high quality. Many companies working with pure software systems have adopted these principles, but implementing them in companies dealing with non-pure software products is challenging. We identified a set of goals and practices to support large-scale agile development in companies that develop software-intense mechatronic systems. We used an inductive approach based on empirical data collected during a longitudinal study with six companies in the Nordic region. The data collection took place over two years through focus group workshops, individual on-site interviews, and complementary surveys. The primary benefit of large-scale agile development is improved quality, enabled by practices that support regular or continuous integration between teams delivering software, hardware, and mechanics. In this regard, the most beneficial integration cycle for deliveries is every four weeks, while continuous integration on a daily basis would favor software teams, other disciplines does not seem to benefit from faster integration cycles. We identified 108 goals and development practices supporting agile principles among the companies, most of them concerned with integration, therefrom, 26 agile practices are unique to the mechatronics domain to support adopting agile beyond pure software development teams. 16 of these practices are considered as key enablers, confirmed by our control cases.