nils-herrmann/clean_scirepeval huggingface dataset:
A Hybrid Spectral Clustering and Deep Neural Network Ensemble Algorithm for Intrusion Detection in Sensor Networks

The development of intrusion detection systems (IDS) that are adapted to allow routers and network defence systems to detect malicious network traffic disguised as network protocols or normal access is a critical challenge. This paper proposes a novel approach called SCDNN, which combines spectral clustering (SC) and deep neural network (DNN) algorithms. First, the dataset is divided into k subsets based on sample similarity using cluster centres, as in SC. Next, the distance between data points in a testing set and the training set is measured based on similarity features and is fed into the deep neural network algorithm for intrusion detection. Six KDD-Cup99 and NSL-KDD datasets and a sensor network dataset were employed to test the performance of the model. These experimental results indicate that the SCDNN classifier not only performs better than backpropagation neural network (BPNN), support vector machine (SVM), random forest (RF) and Bayes tree models in detection accuracy and the types of abnormal attacks found. It also provides an effective tool of study and analysis of intrusion detection in large networks.
An Effective Path Selection Strategy for Mutation Testing

Mutation testing has been identified as one of the most effective techniques, in detecting faults. However, because of the large number of test elements that it introduces, it is regarded as rather expensive for practical use. Therefore, there is a need for testing strategies that will alleviate this drawback by selecting effective test data that will make the technique more practical. Such a strategy based on path selection is reported in this paper. A significant influence on the efficiency associated with path selection strategies is the number of test paths that must be generated in order to achieve a specified level of coverage, and it is determined by the number of paths that are found to be feasible. Specifically, a path selection strategy is proposed that aims at reducing the effects of infeasible paths and conversely developing effective and efficient mutation based tests. The results obtained from applying the method to a set of program units are reported and analysed presenting the flexibility, feasibility and practicality of the proposed approach.
The role of microRNAs in respiratory viral infection: friend or foe?

MicroRNAs (miRNAs) have emerged as a class of regulatory RNAs in host-pathogen interactions. Aberrant miRNA expression seems to play a central role in the pathology of several respiratory viruses, promoting development and progression of infection. miRNAs may thus serve as therapeutic and prognostic factors for respiratory viral infectious disease caused by a variety of agents. We present a comprehensive review of recent findings related to the role of miRNAs in different respiratory viral infections and discuss possible therapeutic opportunities aiming to attenuate the burden of viral infections. Our review supports the emerging concept that cellular and viral-encoded miRNAs might be broadly implicated in human respiratory viral infections, with either positive or negative effects on virus life cycle.
Recognizing Textures with Mobile Cameras for Pedestrian Safety Applications

As smartphone rooted distractions become commonplace, the lack of compelling safety measures has led to a rise in the number of injuries to distracted walkers. Various solutions address this problem by sensing a pedestrian’s walking environment. Existing camera-based approaches have been largely limited to obstacle detection and other forms of object detection. Instead, we present TerraFirma, an approach that performs material recognition on the pedestrian’s walking surface. We explore, first, how well commercial off-the-shelf smartphone cameras can learn texture to distinguish among paving materials in uncontrolled outdoor urban settings. Second, we aim at identifying when a distracted user is about to enter the street, which can be used to support safety functions such as warning the user to be cautious. To this end, we gather a unique dataset of street/sidewalk imagery from a pedestrian’s perspective, that spans major cities like New York, Paris, and London. We demonstrate that modern phone cameras can be enabled to distinguish materials of walking surfaces in urban areas with more than 90% accuracy, and accurately identify when pedestrians transition from sidewalk to street.
Strategic planning for information services at multi-facility health systems.

Without benefit of an up-to-date, in-depth appraisal of any specific multi-facility's organization, the healthcare facility's mission statement and philosophy, and a detailed understanding of the current situation within each of the IS divisions and/or Data Processing departments, it is merely possible to generically assess the needs in light of today's readily available technology, and to subjectively and logically apply ones past experience to determine a preferred approach. Therefore, this overview of strategic planning considerations ought to be used with caution. A workable plan requires extensive on-going effort, and comes alive only when it is adopted by management. In the event that no previous information services planning activity has occurred within the organization, or where a prior strategic plan is more than three years old, prudent advice would include a strong recommendation to begin such a process without delay.
Metabolic acidosis in restraint-associated cardiac arrest: a case series.

The mechanism of death in patients struggling against restraints remains a topic of debate. This article presents a series of five patients with restraint-associated cardiac arrest and profound metabolic acidosis. The lowest recorded pH was 6.25; this patient and three others died despite aggressive resuscitation. The survivor's pH was 6.46; this patient subsequently made a good recovery. Struggling against restraints may produce a lactic acidosis. Stimulant drugs such as cocaine may promote further metabolic acidosis and impair normal behavioral regulatory responses. Restrictive positioning of combative patients may impede appropriate respiratory compensation for this acidemia. Public safety personnel and emergency providers must be aware of the life threat to combative patients and be careful with restraint techniques. Further investigation of sedative agents and buffering therapy for this select patient group is suggested.
Dimension Reduction in Text Classification with Support Vector Machines

Support vector machines (SVMs) have been recognized as one o f th most successful classification methods for many applications including text classific ation. Even though the learning ability and computational complexity of training in support vector machines may be independent of the dimension of the feature space, reducing computational com plexity is an essential issue to efficiently handle a large number of terms in practical applicat ions of text classification. In this paper, we adopt novel dimension reduction methods to reduce the dim nsion of the document vectors dramatically. We also introduce decision functions for the centroid-based classification algorithm and support vector classifiers to handle the classification p r blem where a document may belong to multiple classes. Our substantial experimental results sh ow t at with several dimension reduction methods that are designed particularly for clustered data, higher efficiency for both training and testing can be achieved without sacrificing prediction accu ra y of text classification even when the dimension of the input space is significantly reduced.
Redundancy and Diversity in Security

Redundancy and diversity are commonly applied principles for fault tolerance against accidental faults. Their use in security, which is attracting increasing interest, is less general and less of an accepted principle. In particular, redundancy without diversity is often argued to be useless against systematic attack, and diversity to be of dubious value. This paper discusses their roles and limits, and to what extent lessons from research on their use for reliability can be applied to security, in areas such as intrusion detection. We take a probabilistic approach to the problem, and argue its validity for security. We then discuss the various roles of redundancy and diversity for security, and show that some basic insights from probabilistic modelling in reliability and safety indeed apply to examples of design for security. We discuss the factors affecting the efficacy of redundancy and diversity, the role of “independence” between layers of defense, and some of the trade-offs facing designers.
A double take on bivalent promoters.

Histone modifications and chromatin-associated protein complexes are crucially involved in the control of gene expression, supervising cell fate decisions and differentiation. Many promoters in embryonic stem (ES) cells harbor a distinctive histone modification signature that combines the activating histone H3 Lys 4 trimethylation (H3K4me3) mark and the repressive H3K27me3 mark. These bivalent domains are considered to poise expression of developmental genes, allowing timely activation while maintaining repression in the absence of differentiation signals. Recent advances shed light on the establishment and function of bivalent domains; however, their role in development remains controversial, not least because suitable genetic models to probe their function in developing organisms are missing. Here, we explore avenues to and from bivalency and propose that bivalent domains and associated chromatin-modifying complexes safeguard proper and robust differentiation.
Distributional Sentence Entailment Using Density Matrices

Categorical compositional distributional model of [9] sug gests a way to combine grammatical composition of the formal, type logi cal models with the corpus based, empirical word representations of distribut ional semantics. This paper contributes to the project by expanding the model to al so capture entailment relations. This is achieved by extending the representatio s of words from points in meaning space to density operators, which are probabilit y d stributions on the subspaces of the space. A symmetric measure of similarity an d an asymmetric measure of entailment is defined, where lexical entailment i s measured using von Neumann entropy, the quantum variant of Kullback-Leibl er divergence. Lexical entailment, combined with the composition map on wo rd representations, provides a method to obtain entailment relations on the leve l of sentences. Truth theoretic and corpus-based examples are provided.
PASSENGER AND BAGGAGE FLOW IN AN AIRPORT TERMINAL : A FLEXIBLE SIMULATION MODEL

The lack of a friendly and flexible operational model of landside operations motivated the creation of a new simulation model adaptable to various airport configurations for estimating the time behavior of passenger and baggage flows, the elements’ capacities and the delays in a generic airport terminal. The validation of the model has been conducted by comparison with the results of previous research about the average behavior of the future Athens airport. In the mean time the proposed model provided interesting dynamical results about both passenger and baggage movements in the system.
Bilateral robotic priming before task-oriented approach in subacute stroke rehabilitation: a pilot randomized controlled trial.

To investigate the treatment effects of bilateral robotic priming combined with the task-oriented approach on motor impairment, disability, daily function, and quality of life in patients with subacute stroke.



A randomized controlled trial.



Occupational therapy clinics in medical centers.



Thirty-one subacute stroke patients were recruited.



Participants were randomly assigned to receive bilateral priming combined with the task-oriented approach (i.e., primed group) or to the task-oriented approach alone (i.e., unprimed group) for 90 minutes/day, 5 days/week for 4 weeks. The primed group began with the bilateral priming technique by using a bimanual robot-aided device.



Motor impairments were assessed by the Fugal-Meyer Assessment, grip strength, and the Box and Block Test. Disability and daily function were measured by the modified Rankin Scale, the Functional Independence Measure, and actigraphy. Quality of life was examined by the Stroke Impact Scale.



The primed and unprimed groups improved significantly on most outcomes over time. The primed group demonstrated significantly better improvement on the Stroke Impact Scale strength subscale ( p = 0.012) and a trend for greater improvement on the modified Rankin Scale ( p = 0.065) than the unprimed group.



Bilateral priming combined with the task-oriented approach elicited more improvements in self-reported strength and disability degrees than the task-oriented approach by itself. Further large-scale research with at least 31 participants in each intervention group is suggested to confirm the study findings.
Multi-level Semantic Labelling of Numerical Values

With the success of Open Data a huge amount of tabular data sources became available that could potentially be mapped and linked into the Web of (Linked) Data. Most existing approaches to “semantically label” such tabular data rely on mappings of textual information to classes, properties, or instances in RDF knowledge bases in order to link – and eventually transform – tabular data into RDF. However, as we will illustrate, Open Data tables typically contain a large portion of numerical columns and/or non-textual headers; therefore solutions that solely focus on textual “cues” are only partially applicable for mapping such data sources. We propose an approach to find and rank candidates of semantic labels and context descriptions for a given bag of numerical values. To this end, we apply a hierarchical clustering over information taken from DBpedia to build a background knowledge graph of possible “semantic contexts” for bags of numerical values, over which we perform a nearest neighbour search to rank the most likely candidates. Our evaluation shows that our approach can assign fine-grained semantic labels, when there is enough supporting evidence in the background knowledge graph. In other cases, our approach can nevertheless assign high level contexts to the data, which could potentially be used in combination with other approaches to narrow down the search space of possible labels.
Detection of Malicious Scripting Code Through Discriminant and Adversary-Aware API Analysis

JavaScript and ActionScript are powerful scripting languages that do not only allow the delivery of advanced multimedia contents, but that can be also used to exploit critical vulnerabilities of third-party applications. To detect both ActionScriptand JavaScript-based malware, we propose in this paper a machine-learning methodology that is based on extracting discriminant information from system API methods, attributes and classes. Our strategy exploits the similarities between the two scripting languages, and has been devised by also considering the possibility of targeted attacks that aim to deceive the employed classification algorithms. We tested our method on PDF and SWF data, respectively embedding JavaScript and ActionScript codes. Results show that the proposed strategy allows us to detect most of the tested malicious files, with low false positive rates. Finally, we show that the proposed methodology is also reasonably robust against evasive and targeted attacks.
Prediction of Aggressive Comments in Social Media: an Exploratory Study

This paper presents a set of techniques for predicting aggressive comments in social media. In a time when cyberbullying has, unfortunately, made its entrance into society and Internet, it becomes necessary to find ways for preventing and overcoming this phenomenon. One of these concerns the use of machine learning techniques for automatically detecting cases of cyberbullying; a primary task within this cyberbullying detection consists of aggressive text detection. We concretely explore different computational techniques for carrying out this task, either as a classification or as a regression problem, and our results suggest that a key feature is the identification of profane words.
Biosynthesis of the Pseudomonas aeruginosa Extracellular Polysaccharides, Alginate, Pel, and Psl

Pseudomonas aeruginosa thrives in many aqueous environments and is an opportunistic pathogen that can cause both acute and chronic infections. Environmental conditions and host defenses cause differing stresses on the bacteria, and to survive in vastly different environments, P. aeruginosa must be able to adapt to its surroundings. One strategy for bacterial adaptation is to self-encapsulate with matrix material, primarily composed of secreted extracellular polysaccharides. P. aeruginosa has the genetic capacity to produce at least three secreted polysaccharides; alginate, Psl, and Pel. These polysaccharides differ in chemical structure and in their biosynthetic mechanisms. Since alginate is often associated with chronic pulmonary infections, its biosynthetic pathway is the best characterized. However, alginate is only produced by a subset of P. aeruginosa strains. Most environmental and other clinical isolates secrete either Pel or Psl. Little information is available on the biosynthesis of these polysaccharides. Here, we review the literature on the alginate biosynthetic pathway, with emphasis on recent findings describing the structure of alginate biosynthetic proteins. This information combined with the characterization of the domain architecture of proteins encoded on the Psl and Pel operons allowed us to make predictive models for the biosynthesis of these two polysaccharides. The results indicate that alginate and Pel share certain features, including some biosynthetic proteins with structurally or functionally similar properties. In contrast, Psl biosynthesis resembles the EPS/CPS capsular biosynthesis pathway of Escherichia coli, where the Psl pentameric subunits are assembled in association with an isoprenoid lipid carrier. These models and the environmental cues that cause the cells to produce predominantly one polysaccharide over the others are subjects of current investigation.
SemEval-2013 Task 4: Free Paraphrases of Noun Compounds

In this paper, we describe SemEval-2013 Task 4: the definition, the data, the evaluation and the results. The task is to capture some of the meaning of English noun compounds via paraphrasing. Given a two-word noun compound, the participating system is asked to produce an explicitly ranked list of its free-form paraphrases. The list is automatically compared and evaluated against a similarly ranked list of paraphrases proposed by human annotators, recruited and managed through Amazon’s Mechanical Turk. The comparison of raw paraphrases is sensitive to syntactic and morphological variation. The “gold” ranking is based on the relative popularity of paraphrases among annotators. To make the ranking more reliable, highly similar paraphrases are grouped, so as to downplay superficial differences in syntax and morphology. Three systems participated in the task. They all beat a simple baseline on one of the two evaluation measures, but not on both measures. This shows that the task is difficult.
Skewness from High-Frequency Data Predicts the Cross-Section of Stock Returns Diego

Theoretical and empirical research documents a negative relation between the cross-section of stock returns and individual skewness. Individual skewness has been dened with coskewness, industry groups, predictive models, and even with options skewness. However, measures of skewness computed only from stock returns, such as historical skewness, do not conrm this negative relation. In this paper, we propose a model-free measure of individual stock skewness directly obtained from high-frequency intraday prices, which we call realized skewness. We hypothesize that realized skewness predicts future stock returns. To test this hypothesis, we sort stocks every week according to realized skewness, form ve portfolios and analyze subsequent weekly returns. We nd a negative relation between realized skewness and stock returns in the cross section. A trading strategy that buys stocks in the lowest realized skewness quintile and sells stocks in the highest realized skewness quintile generates an average raw return of 38 basis points per week with a t-statistic of 9.15. This result is robust to di¤erent market periods, portfolio weightings, rm characteristics and is not explained by linear factor models. Comments are welcome. We both want to thank IFM for nancial support. Any remaining inadequacies are ours alone. Correspondence to: Aurelio Vasquez, Faculty of Management, McGill University, 1001 Sherbrooke Street West, Montreal, Quebec, Canada, H3A 1G5; Tel: (514) 398-4000 x.00231; E-mail: Aurelio.Vasquez@mcgill.ca.
A 77-GHz FMCW radar transceiver sourced through a 19-GHz SiGe Colpitts oscillator

An integrated 19-GHz Colpitts oscillator for a 77-GHz FMCW automotive radar frontend application is presented. The Colpitts oscillator has been realized in a fully differential circuit architecture. The VCO's 19 GHz output signal is buffered with an emitter follower stage and used as a LO signal source for a 77-GHz radar transceiver architecture. The LO frequency is quadrupled and amplified to drive the switching quad of a Gilbert-type mixer. As the quadrupler-mixer chip is required to describe the radar-sensor it is introduced, but the main focus of this paper aims the design of the sensor's LO source. In addition, the VCO-chip provides a divide-by-8 stage. The divider is either used for on-wafer measurements or later on in a PLL application.
Biologically oriented preparation technique (BOPT): a new approach for prosthetic restoration of periodontically healthy teeth.

Tooth preparations for fixed prosthetic restorations can be done in different ways, basically of two kinds: preparation with a defined margin and the so-called vertical preparation or feather edge. The latter was originally used for prosthetics on teeth treated with resective surgery for periodontal disease. In this article, the author presents a prosthetic technique for periodontally healthy teeth using feather edge preparation in a flapless approach in both esthetic and posterior areas with ceramometal and zirconia restorations, achieving high quality clinical and esthetic results in terms of soft tissue stability at the prosthetic/tissue interface, both in the short and in the long term (clinical follow-up up to fifteen years). Moreover, the BOPT technique, if compared to other preparation techniques (chamfer, shoulder, etc), is simpler and faster when in preparation impression taking, temporary crowns' relining and creating the crowns' profiles up to the final prosthetic restoration.
Distinct myeloid progenitor differentiation pathways identified through single cell RNA sequencing

According to current models of hematopoiesis, lymphoid-primed multi-potent progenitors (LMPPs) (Lin−Sca-1+c-Kit+CD34+Flt3hi) and common myeloid progenitors (CMPs) (Lin−Sca-1+c-Kit+CD34+CD41hi) establish an early branch point for separate lineage-commitment pathways from hematopoietic stem cells, with the notable exception that both pathways are proposed to generate all myeloid innate immune cell types through the same myeloid-restricted pre–granulocyte-macrophage progenitor (pre-GM) (Lin−Sca-1−c-Kit+CD41−FcγRII/III−CD150−CD105−). By single-cell transcriptome profiling of pre-GMs, we identified distinct myeloid differentiation pathways: a pathway expressing the gene encoding the transcription factor GATA-1 generated mast cells, eosinophils, megakaryocytes and erythroid cells, and a pathway lacking expression of that gene generated monocytes, neutrophils and lymphocytes. These results identify an early hematopoietic-lineage bifurcation that separates the myeloid lineages before their segregation from other hematopoietic-lineage potential.