nils-herrmann/clean_scirepeval huggingface dataset:
Detecting routing anomalies with RIPE Atlas

Routing anomalies are a common occurrence on Today’s Internet. Given the vast size of the Internet, detecting such anomalies requires having a large set of vantage points from which to be able to schedule detection tests. An initiative of the RIPE NCC, RIPE Atlas is a globally distributed Internet measurement system that offers a favorable number vantage points. The project examines whether the technical capabilities of RIPE Atlas can be instrumented for the detection of three types of routing anomalies, namely Debogon filtering, Internet censorship and BGP prefix hijacking. By examining existing methodologies for detecting routing anomalies, the project defines a number of tests in RIPE Atlas. The tests examine whether RIPE Atlas is a viable replacement to current detection system and what limitations it presents.
"Breaking" Disasters: Predicting and Characterizing the Global News Value of Natural and Man-made Disasters

Due to their often unexpected nature, natural and man-made disasters are difficult to monitor and detect for journalists and disaster management response teams. Journalists are increasingly relying on signals from social media to detect such stories in their early stage of development. Twitter, which features a vast network of local news outlets, is a major source of early signal for disaster detection. Journalists who work for global desks often follow these sources via Twitter’s lists, but have to comb through thousands of small-scale or low-impact stories to find events that may be globally relevant. These are events that have a large scope, high impact, or potential geo-political relevance. We propose a model for automatically identifying events from local news sources that may break on a global scale within the next 24 hours. The results are promising and can be used in a predictive setting to help journalists manage their sources more effectively, or in a descriptive manner to analyze media coverage of disasters. Through the feature evaluation process, we also address the question: “what makes a disaster event newsworthy on a global scale?” As part of our data collection process, we have created a list of local sources of disaster/accident news on Twitter, which we have made publicly available.
Decentralized control of Partially Observable Markov Decision Processes using belief space macro-actions

The focus of this paper is on solving multi-robot planning problems in continuous spaces with partial observability. Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) are general models for multi-robot coordination problems, but representing and solving Dec-POMDPs is often intractable for large problems. To allow for a high-level representation that is natural for multi-robot problems and scalable to large discrete and continuous problems, this paper extends the Dec-POMDP model to the Decentralized Partially Observable Semi-Markov Decision Process (Dec-POSMDP). The Dec-POSMDP formulation allows asynchronous decision-making by the robots, which is crucial in multi-robot domains. We also present an algorithm for solving this Dec-POSMDP which is much more scalable than previous methods since it can incorporate closed-loop belief space macro-actions in planning. These macro-actions are automatically constructed to produce robust solutions. The proposed method's performance is evaluated on a complex multi-robot package delivery problem under uncertainty, showing that our approach can naturally represent multi-robot problems and provide high-quality solutions for large-scale problems.
Comparing Policy Gradient and Value Function Based Reinforcement Learning Methods in Simulated Electrical Power Trade

In electrical power engineering, reinforcement learning algorithms can be used to model the strategies of electricity market participants. However, traditional value function based reinforcement learning algorithms suffer from convergence issues when used with value function approximators. Function approximation is required in this domain to capture the characteristics of the complex and continuous multivariate problem space. The contribution of this paper is the comparison of policy gradient reinforcement learning methods, using artificial neural networks for policy function approximation, with traditional value function based methods in simulations of electricity trade. The methods are compared using an AC optimal power flow based power exchange auction market model and a reference electric power system model.
Removing camera shake from a single photograph

Camera shake during exposure leads to objectionable image blur and ruins many photographs. Conventional blind deconvolution methods typically assume frequency-domain constraints on images, or overly simplified parametric forms for the motion path during camera shake. Real camera motions can follow convoluted paths, and a spatial domain prior can better maintain visually salient image characteristics. We introduce a method to remove the effects of camera shake from seriously blurred images. The method assumes a uniform camera blur over the image and negligible in-plane camera rotation. In order to estimate the blur from the camera shake, the user must specify an image region without saturation effects. We show results for a variety of digital photographs taken from personal photo collections.
The effect of threshold values on association rule based classification accuracy

Classification Association Rule Mining (CARM) systems operate by applying an Association Rule Mining (ARM) method to obtain classification rules from a training set of previously-classified data. The rules thus generated will be influenced by the choice of ARM parameters employed by the algorithm (typically support and confidence threshold values). In this paper we examine the effect that this choice has on the predictive accuracy of CARM methods. We show that the accuracy can almost always be improved by a suitable choice of parameters, and describe a hill-climbing method for finding the best parameter settings. We also demonstrate that the proposed hill-climbing method is most effective when coupled with a fast CARM algorithm such as the TFPC algorithm which is also described.
Bandwidth and resolution enhancement through pulse compression

A novel pulse compression technique is developed that improves the axial resolution of an ultrasonic imaging system and provides a boost in the echo signal-to-noise ratio (eSNR). The new technique, called the resolution enhancement compression (REC) technique, was validated with simulations and experimental measurements. Image quality was examined in terms of three metrics: the cSNR, the bandwidth, and the axial resolution through the modulation transfer function (MTF). Simulations were conducted with a weakly-focused, single-element ultrasound source with a center frequency of 2.25 MHz. Experimental measurements were carried out with a single-element transducer (f/3) with a center frequency of 2.25 MHz from a planar reflector and wire targets. In simulations, axial resolution of the ultrasonic imaging system was almost doubled using the REC technique (0.29 mm) versus conventional pulsing techniques (0.60 mm). The -3 dB pulse/echo bandwidth was more than doubled from 48% to 97%, and maximum range sidelobes were -40 dB. Experimental measurements revealed an improvement in axial resolution using the REC technique (0.31 mm) versus conventional pulsing (0.44 mm). The -3 dB pulse/echo bandwidth was doubled from 56% to 113%, and maximum range sidelobes were observed at -45 dB. In addition, a significant gain in eSNR (9 to 16.2 dB) was achieved
Results of vertical figure-of-eight tension band suture for finger nail disruptions with fractures of distal phalanx

Fingertip injuries involve varying degree of fractures of the distal phalanx and nail bed or nail plate disruptions. The treatment modalities recommended for these injuries include fracture fixation with K-wire and meticulous repair of nail bed after nail removal and later repositioning of nail or stent substitute into the nail fold by various methods. This study was undertaken to evaluate the functional outcome of vertical figure-of-eight tension band suture for finger nail disruptions with fractures of distal phalanx.



A series of 40 patients aged between 4 and 58 years, with 43 fingernail disruptions and fracture of distal phalanges, were treated with vertical figure-of-eight tension band sutures without formal fixation of fracture fragments and the results were reviewed. In this method, the injuries were treated by thoroughly cleaning the wound, reducing the fracture fragments, anatomical replacement of nail plate, and securing it by vertical figure-of-eight tension band suture.



All patients were followed up for a minimum of 3 months. The clinical evaluation of the patients was based on radiological fracture union and painless pinch to determine fingertip stability. Every single fracture united and every fingertip was clinically stable at the time of final followup. We also evaluated our results based on visual analogue scale for pain and range of motion of distal interphalangeal joint. Two sutures had to be revised due to over tensioning and subsequent vascular compromise within minutes of repair; however, this did not affect the final outcome.



This technique is simple, secure, and easily reproducible. It neither requires formal repair of injured nail bed structures nor fixation of distal phalangeal fracture and results in uncomplicated reformation of nail plate and uneventful healing of distal phalangeal fractures.
Comparing Cortical Plasticity Induced by Conventional and High-Definition 4 × 1 Ring tDCS: A Neurophysiological Study

Transcranial direct current stimulation (tDCS) induces long-lasting NMDA receptor-dependent cortical plasticity via persistent subthreshold polarization of neuronal membranes. Conventional bipolar tDCS is applied with two large (35 cm(2)) rectangular electrodes, resulting in directional modulation of neuronal excitability. Recently a newly designed 4 × 1 high-definition (HD) tDCS protocol was proposed for more focal stimulation according to the results of computational modeling. HD tDCS utilizes small disc electrodes deployed in 4 × 1 ring configuration whereby the physiological effects of the induced electric field are thought to be grossly constrained to the cortical area circumscribed by the ring.



We aim to compare the physiological effects of both tDCS electrode arrangements on motor cortex excitability.



tDCS was applied with 2 mA for 10 min. Fourteen healthy subjects participated, and motor cortex excitability was monitored by transcranial magnetic stimulation (TMS) before and after tDCS.



Excitability enhancement following anodal and a respective reduction after cathodal stimulation occurred in both, conventional and HD tDCS. However, the plastic changes showed a more delayed peak at 30 min and longer lasting after-effects for more than 2 h after HD tDCS for both polarities, as compared to conventional tDCS.



The results show that this new electrode arrangement is efficient for the induction of neuroplasticity in the primary motor cortex. The pattern of aftereffects might be compatible with the concept of GABA-mediated surround inhibition, which should be explored in future studies directly.
Cross-lingual Projected Expectation Regularization for Weakly Supervised Learning

We consider a multilingual weakly supervised learning scenario where knowledge from annotated corpora in a resource-rich language is transferred via bitext to guide the learning in other languages. Past approaches project labels across bitext and use them as features or gold labels for training. We propose a new method that projects model expectations rather than labels, which facilities transfer of model uncertainty across language boundaries. We encode expectations as constraints and train a discriminative CRF model using Generalized Expectation Criteria (Mann and McCallum, 2010). Evaluated on standard Chinese-English and German-English NER datasets, our method demonstrates F1 scores of 64% and 60% when no labeled data is used. Attaining the same accuracy with supervised CRFs requires 12k and 1.5k labeled sentences. Furthermore, when combined with labeled examples, our method yields significant improvements over state-of-the-art supervised methods, achieving best reported numbers to date on Chinese OntoNotes and German CoNLL-03 datasets.
Lexical Chains as Document Features

Document clustering and classification is usually done by representing the documents using a bag of words scheme. This scheme ignores many of the linguistic and semantic features contained in text documents. We propose here an alternative representation for documents using Lexical Chains. We compare the performance of the new representation against the old one on a clustering task. We show that Lexical Chain based features give better results than the Bag of Words based features, while achieving almost 30% reduction in the dimensionality of the feature vectors resulting in faster execution of the algorithms.
Association of Food Insecurity with Children's Behavioral, Emotional, and Academic Outcomes: A Systematic Review.

Food Insecurity (FI) occurs in 21% of families with children and adolescents in the United States, but the potential developmental and behavioral implications of this prevalent social determinant of health have not been comprehensively elucidated. This systematic review aims to examine the association between FI and childhood developmental and behavioral outcomes in western industrialized countries.



This review provides a critical summary of 23 peer reviewed articles from developed countries on the associations between FI and adverse childhood developmental behavioral outcomes including early cognitive development, academic performance, inattention, externalizing behaviors, and depression in 4 groups-infants and toddlers, preschoolers, school age, and adolescents. Various approaches to measuring food insecurity are delineated. Potential confounding and mediating variables of this association are compared across studies. Alternate explanatory mechanisms of observed effects and need for further research are discussed.



This review demonstrates that household FI, even at marginal levels, is associated with children's behavioral, academic, and emotional problems from infancy to adolescence across western industrialized countries - even after controlling for confounders.



While the American Academy of Pediatrics already recommends routine screening for food insecurity during health maintenance visits, the evidence summarized here should encourage developmental behavioral health providers to screen for food insecurity in their practices and intervene when possible. Conversely, children whose families are identified as food insecure in primary care settings warrant enhanced developmental behavioral assessment and possible intervention.
Hybrid System for fouling control in biomass boilers

Renewable energy sources are essential paths towards sustainable development and CO2 emission reduction. For example, the European Union has set the target of achieving 22% of electricity generation from renewable sources by 2010. However, the extensive use of this energy source is being avoided by some technical problems as fouling and slagging in the surfaces of boiler heat exchangers. Although these phenomena were extensively studied in the last decades in order to optimize the behaviour of large coal power boilers, a simple, general and effective method for fouling control has not been developed. For biomass boilers, the feedstock variability and the presence of new components in ash chemistry increase the fouling influence in boiler performance. In particular, heat transfer is widely affected and the boiler capacity becomes dramatically reduced. Unfortunately, the classical approach of regular sootblowing cycles becomes clearly insufficient for them. Artificial Intelligence (AI) provides new means to undertake this problem. This paper illustrates a methodology based on Neural Networks (NNs) and Fuzzy-Logic Expert Systems to select the moment for activating sootblowing in an industrial biomass boiler. The main aim is to minimize the boiler energy and efficiency losses with a proper sootblowing activation. Although the NN type used in this work is well-known and the Hybrid Systems had been extensively used in the last decade, the excellent results obtained in the use of AI in industrial biomass boilers control with regard to previous approaches makes this work a novelty.
IEEE 802.15.4 security sublayer for OMNET++

Most network simulators do not support security features. In this paper, we introduce a new security module for OMNET++ that implements the IEEE 802.15.4 security suite. This module, developed using the C++ language, can simulate all devices and sensors that implement the IEEE 802.15.4 standard. The OMNET++ security module is also evaluated in terms of quality of services in the presence of physical hop attacks. Results show that our module is reliable and can safely be used by researchers.
SOA maturity model a frame of reference

Service Oriented Architecture (SOA) is an architectural style that supports service orientation. In reality, SOA is much more than architecture. SOA adoption is prerequisite for organization to excel their service deliveries, as the delivery platforms are shifting to mobile, cloud and social media. A maturity model is a tool to accelerate enterprise SOA adoption, however it depends on how it should be applied. This paper presents a literature review of existing maturity models and proposes 5 major aspects that a maturity model has to address to improve SOA practices of an enterprise. A maturity model can be used as: (i) a roadmap for SOA adoption, (ii) a reference guide for SOA adoption, (iii) a tool to gauge maturity of process execution, (iv) a tool to measure the effectiveness of SOA motivations, and (v) a review tool for governance framework. This paper also sheds light on how SOA maturity assessment can be modeled. A model for SOA process execution maturity and perspective maturity assessment has been proposed along with a framework to include SOA scope of adoption.
Effects of leucine and its metabolite β-hydroxy-β-methylbutyrate on human skeletal muscle protein metabolism

Maintenance of skeletal muscle mass is contingent upon the dynamic equilibrium (fasted losses-fed gains) in protein turnover. Of all nutrients, the single amino acid leucine (Leu) possesses the most marked anabolic characteristics in acting as a trigger element for the initiation of protein synthesis. While the mechanisms by which Leu is 'sensed' have been the subject of great scrutiny, as a branched-chain amino acid, Leu can be catabolized within muscle, thus posing the possibility that metabolites of Leu could be involved in mediating the anabolic effect(s) of Leu. Our objective was to measure muscle protein anabolism in response to Leu and its metabolite HMB. Using [1,2-(13)C2]Leu and [(2)H5]phenylalanine tracers, and GC-MS/GC-C-IRMS we studied the effect of HMB or Leu alone on MPS (by tracer incorporation into myofibrils), and for HMB we also measured muscle proteolysis (by arteriovenous (A-V) dilution). Orally consumed 3.42 g free-acid (FA-HMB) HMB (providing 2.42 g of pure HMB) exhibited rapid bioavailability in plasma and muscle and, similarly to 3.42 g Leu, stimulated muscle protein synthesis (MPS; HMB +70% vs. Leu +110%). While HMB and Leu both increased anabolic signalling (mechanistic target of rapamycin; mTOR), this was more pronounced with Leu (i.e. p70S6K1 signalling 90 min vs. 30 min for HMB). HMB consumption also attenuated muscle protein breakdown (MPB; -57%) in an insulin-independent manner. We conclude that exogenous HMB induces acute muscle anabolism (increased MPS and reduced MPB) albeit perhaps via distinct, and/or additional mechanism(s) to Leu.
Taking Arduino to the Internet of Things: The ASIP programming model

Micro-controllers such as Arduino are widely used by all kinds of makers worldwide. Popularity has been driven by Arduino’s simplicity of use and the large number of sensors and libraries available to extend the basic capabilities of these controllers. The last decade has witnessed a surge of software engineering solutions for “the Internet of Things”, but in several cases these solutions require computational resources that are more advanced than simple, resource-limited micro-controllers. Surprisingly, in spite of being the basic ingredients of complex hardware-software systems, there does not seem to be a simple and flexible way to (1) extend the basic capabilities of micro-controllers, and (2) to coordinate inter-connected micro-controllers in “the Internet of Things”. Indeed, new capabilities are added on a per-application basis and interactions are mainly limited to bespoke, point-to-point protocols that target the hardware I/O rather than the services provided by this hardware. In this paper we present the Arduino Service Interface Programming (ASIP) model, a new model that addresses the issues above by (1) providing a “Service” abstraction to easily add new capabilities to micro-controllers, and (2) providing support for networked boards using a range of strategies, including socket connections, bridging devices, MQTT-based publish-subscribe messaging, discovery services, etc. We provide an open-source implementation of the code running on Arduino boards and client libraries in Java, Python, Racket and Erlang. We show how ASIP enables the rapid development of non-trivial applications (coordination of input/output on distributed boards and implementation of a line-following algorithm for a remote robot) and we assess the performance of ASIP in several ways, both quantitative and qualitative.
Preparing Instructors for Quality Online Instruction.

With a growing number of courses offered online and degrees offered through the Internet, there is a considerable interest in online education, particularly as it relates to the quality of online instruction. The major concerns are centering on the following questions: What will be the new role for instructors in online education? How will students' learning outcomes be assured and improved in online learning environment? How will effective communication and interaction be established with students in the absence of face-to-face instruction? How will instructors motivate students to learn in the online learning environment? This paper will examine new challenges and barriers for online instructors, highlight major themes prevalent in the literature related to “quality control or assurance” in online education, and provide practical strategies for instructors to design and deliver effective online instruction. Recommendations will be made on how to prepare instructors for quality online instruction.