nils-herrmann/clean_scirepeval huggingface dataset:
A New Trust Reputation System for E-Commerce Applications

Robust Trust Reputation Systems (TRS) provide a most trustful reputation score for a specific product or service so as to support relying parties taking the right decision while interacting with an e-commerce application. Thus, TRS must rely on an appropriate architecture and suitable algorithms that are able to improve the selection, storage, generation and classification of textual feedbacks. In this work, we propose a new architecture for TRS in e-commerce applications. In fact, we propose an intelligent layer which displays to each feedback provider, who has already given his recommendation on a product, a collection of prefabricated feedbacks related to the same product. Our main contribution in this paper is a Reputation algorithm which studies the user's attitude toward this selection of prefabricated feedbacks. As a result of this study, the reputation algorithm generates better trust degree of the user, trust degree of the feedback and a better global reputation score of the product.
From simulink to SCADE/lustre to TTA: a layered approach for distributed embedded applications

We present a layered end-to-end approach for the design and implementation of embedded software on a distributed platform. The approach comprises a high-level modeling and simulation layer (Simulink), a middle-level programming and validation layer (SCADE/Lustre) and a low-level execution layer (TTA). We provide algorithms and tools to pass from one layer to the next. First, a translator from Simulink to Lustre. Second, a set of real-time and code-distribution extensions to Lustre. Third, implementation techniques for decomposing a Lustre program into tasks and messages, scheduling the tasks and messages on the processors and the bus, distributing the Lustre code on the execution platform, and generating the necessary "glue" code.
An epidemiological study of pulmonary arterial hypertension.

All hospitalisations for pulmonary arterial hypertension (PAH) in the Scottish population were examined to determine the epidemiological features of PAH. These data were compared with expert data from the Scottish Pulmonary Vascular Unit (SPVU). Using the linked Scottish Morbidity Record scheme, data from all adults aged 16-65 yrs admitted with PAH (idiopathic PAH, pulmonary hypertension associated with congenital heart abnormalities and pulmonary hypertension associated with connective tissue disorders) during the period 1986-2001 were identified. These data were compared with the most recent data in the SPVU database (2005). Overall, 374 Scottish males and females aged 16-65 yrs were hospitalised with incident PAH during 1986-2001. The annual incidence of PAH was 7.1 cases per million population. On December 31, 2002, there were 165 surviving cases, giving a prevalence of PAH of 52 cases per million population. Data from the SPVU were available for 1997-2006. In 2005, the last year with a complete data set, the incidence of PAH was 7.6 cases per million population and the corresponding prevalence was 26 cases per million population. Hospitalisation data from the Scottish Morbidity Record scheme gave higher prevalences of pulmonary arterial hypertension than data from the expert centres (Scotland and France). The hospitalisation data may overestimate the true frequency of pulmonary arterial hypertension in the population, but it is also possible that the expert centres underestimate the true frequency.
Elements of Cloud Computing Security

This chapter provides a simplified introduction to cloud computing. This chapter starts by introducing the history of cloud computing and moves on to describe the cloud architecture and operation. This chapter also discusses briefly cloud servicemodels: Infrastructure-as-a-Service, Platform-as-a-Service, and Software-as-a-Service. Clouds are also categorized based on their ownership to private and public clouds. This chapter concludes by explaining the reasons for choosing cloud computing over other technologies by exploring the economic and technological benefits of the cloud.
Drosophila anti-nematode and antibacterial immune regulators revealed by RNA-Seq

Drosophila melanogaster activates a variety of immune responses against microbial infections. However, information on the Drosophila immune response to entomopathogenic nematode infections is currently limited. The nematode Heterorhabditis bacteriophora is an insect parasite that forms a mutualistic relationship with the gram-negative bacteria Photorhabdus luminescens. Following infection, the nematodes release the bacteria that quickly multiply within the insect and produce several toxins that eventually kill the host. Although we currently know that the insect immune system interacts with Photorhabdus, information on interaction with the nematode vector is scarce. Here we have used next generation RNA-sequencing to analyze the transcriptional profile of wild-type adult flies infected by axenic Heterorhabditis nematodes (lacking Photorhabdus bacteria), symbiotic Heterorhabditis nematodes (carrying Photorhabdus bacteria), and Photorhabdus bacteria alone. We have obtained approximately 54 million reads from the different infection treatments. Bioinformatic analysis shows that infection with Photorhabdus alters the transcription of a large number of Drosophila genes involved in translational repression as well in response to stress. However, Heterorhabditis infection alters the transcription of several genes that participate in lipidhomeostasis and metabolism, stress responses, DNA/protein sythesis and neuronal functions. We have also identified genes in the fly with potential roles in nematode recognition, anti-nematode activity and nociception. These findings provide fundamental information on the molecular events that take place in Drosophila upon infection with the two pathogens, either separately or together. Such large-scale transcriptomic analyses set the stage for future functional studies aimed at identifying the exact role of key factors in the Drosophila immune response against nematode-bacteria complexes.
Characterization of biological diversity through analysis of discrete cranial traits.

In the present study, the frequency distributions of 20 discrete cranial traits in 70 major human populations from around the world were analyzed. The principal-coordinate and neighbor-joining analyses of Smith's mean measure of divergence (MMD), based on trait frequencies, indicate that 1). the clustering pattern is similar to those based on classic genetic markers, DNA polymorphisms, and craniometrics; 2). significant interregional separation and intraregional diversity are present in Subsaharan Africans; 3). clinal relationships exist among regional groups; 4). intraregional discontinuity exists in some populations inhabiting peripheral or isolated areas. For example, the Ainu are the most distinct outliers of the East Asian populations. These patterns suggest that founder effects, genetic drift, isolation, and population structure are the primary causes of regional variation in discrete cranial traits. Our results are compatible with a single origin for modern humans as well as the multiregional model, similar to the results of Relethford and Harpending ([1994] . The results presented here provide additional measures of the morphological variation and diversification of modern human populations.
Error bounds for convolutional codes and an asymptotically optimum decoding algorithm

Probability Theory, 2nd ed. Princeton, Optimum reception of binary gaussian signals,” Bell Sys. Tech. 2810, November 1964. 131 T. T. Kadota. “Ootrmum recention of binarv sure and Gaussian signals,” Bell Sys. ?‘ech: J., vol. 44;~~. 1621-1658, October 1965. 141 U. Grenander, ‘Stochastic processes and statistical inference,” Arkiv fiir Matematik, vol. 17, pp. 195-277, 1950. 151 L. A. Zadeh and J. R. Ragazzini, “Optimum filters for the detection of signals in noise,” Proc. IRE, vol. 40, pp. 1223-1231, O,+nhm 1 a.63 161 J. H. Laning and R. H. Battin, Random Processes in Automatic Control. New York: McGraw-Hill. 1956. nn. 269-358. 171 C.. W. Helstrom, “ Solution of the dete&on integral equation for stationary filtered white noise,” The detection of known signals in colored Gaussian noise,” Stanford Electronics Labs.,  T. T. Kadota, “Optimum reception of nf-ary Gaussian signals in Gaussian noise,” Bell. Sys. Tech. 2197, November 1965. [lOI T. T. Kadota, “Term-by-term differentiability of Mercer’s expansion,”  February 1967.
Evidence-based lean logic profiles for conceptual data modelling languages

Multiple logic-based reconstruction of conceptual data modelling languages such as EER, UML Class Diagrams, and ORM exists. They mainly cover various fragments of the languages and none are formalised such that the logic applies simultaneously for all three modelling language families as unifying mechanism. This hampers interchangeability, interoperability, and tooling support. In addition, due to the lack of a systematic design process of the logic used for the formalisation, hidden choices permeate the formalisations that have rendered them incompatible. We aim to address these problems, first, by structuring the logic design process in a methodological way. We generalise and extend the DSL design process to apply to logic language design more generally and, in particular, by incorporating an ontological analysis of language features in the process. Second, availing of this extended process, of evidence gathered of language feature usage, and of computational complexity insights from Description Logics (DL), we specify logic profiles taking into account the ontological commitments embedded in the languages. The profiles characterise the minimum logic structure needed to handle the semantics of conceptual models, enabling the development of interoperability tools. There is no known DL language that matches exactly the features of those profiles and the common core is small (in the tractable ALNI). Although hardly any inconsistencies can be derived with the profiles, it is promising for scalable runtime use of conceptual data models.
Energy-efficient position based routing protocol for mobile ad hoc networks

A MANET is a collection of mobile nodes communicating and cooperating with each other to route a packet from the source to their destinations. A MANET is proposed to support dynamic routing strategies in absence of wired infrastructure and centralized administration. In such networks, limited power in mobile nodes is a big challenge. So energy efficient techniques should be implemented with existing routing protocols to reduce link failure and improve the network lifetime. This paper is presenting an Energy-Efficient Routing protocol that will improve the utilization of link by balancing the energy consumption between utilized and underutilized nodes to meet the above challenge. The protocol deals with various parameters as Residual Energy, Bandwidth, Load and Hop Count for route discovery. The failure of any node in the route when the transmission of data packet is in progress leads to the degradation of the QoS (Quality of Service). To overcome with this issue, the paper proposes two methods for maintenance of the route. The simulation results show that the proposed protocol achieves objectives like minimizing overheads, fast convergence speed, high reliability and gives enhanced results than previous techniques like DSR.
Formulaic Language and Second Language Acquisition : Zipf and the Phrasal Teddy Bear

This article revisits earlier proposals that language learning is, in essence, the learning of formulaic sequences and their interpretations; that this occurs at all levels of granularity from large to small; and that the language system emerges from the statistical abstraction of patterns latent within and across form and function in language usage. It considers recent research in individual differences, the psycholinguistics of language processing, and longitudinal studies of first (L1) and second (L2) language acquisition. The first section reviews studies of individual differences in phonological short-term memory (PSTM) and working memory (WM) and their correlations with vocabulary and grammar acquisition in L2. The second section summarizes evidence that language processing is sensitive to the statistical properties of formulaic language in terms of frequency and transitional probability. The third section examines the definition of formulas and formulaicity using different statistical metrics. The fourth section evaluates longitudinal research in L1 and L2 into the putative developmental sequence commonly proposed in usage-based approaches, from formula to low-scope pattern to creative construction. The final section weighs the implications of the statistical distributions of formulaicity in usage for developmental sequences of language acquisition. Zipf’s law and the “phrasal teddy bear” explain the paradox whereby formulas seed language acquisition and yet learner language is formula-light in comparison to native norms.
Incremental Integer Linear Programming for Non-projective Dependency Parsing

Integer Linear Programming has recently been used for decoding in a number of probabilistic models in order to enforce global constraints. However, in certain applications, such as non-projective dependency parsing and machine translation, the complete formulation of the decoding problem as an integer linear program renders solving intractable. We present an approach which solves the problem incrementally, thus we avoid creating intractable integer linear programs. This approach is applied to Dutch dependency parsing and we show how the addition of linguistically motivated constraints can yield a significant improvement over stateof-the-art.
A Multiband, Mutipolarization Shared-Aperture Antenna: Design and evaluation.

A compact, shared-aperture antenna (SAA) configuration consisting of various planar antennas embedded into a single footprint is presented in this article. An L-probefed, suspended-plate, horizontally polarized antenna operating in an 900-MHz band; an aperture-coupled, vertically polarized, microstrip antenna operating at 4.2-GHz; a 2 &#x000D7; 2 microstrip patch array operating at the X band; a low-side-lobe level (SLL), corporate-fed, 8 &#x000D7; 4 microstrip planar array for synthetic aperture radar (SAR) in the X band; and a printed, single-arm, circularly polarized, tilted-beam spiral antenna operating at the C band are integrated into a single aperture for simultaneous operation. This antenna system could find potential application in many airborne and unmanned aircraft vehicle (UAV) technologies. While the design of these antennas is not that critical, their optimal placement in a compact configuration for simultaneous operation with minimal interference poses a significant challenge to the designer. The placement optimization was arrived at based on extensive numerical fullwave optimizations.
Predicting ICU Mortality Risk by Grouping Temporal Trends from a Multivariate Panel of Physiologic Measurements

ICU mortality risk prediction may help clinicians take effective interventions to improve patient outcome. Existing machine learning approaches often face challenges in integrating a comprehensive panel of physiologic variables and presenting to clinicians interpretable models. We aim to improve both accuracy and interpretability of prediction models by introducing Subgraph Augmented Non-negative Matrix Factorization (SANMF) on ICU physiologic time series. SANMF converts time series into a graph representation and applies frequent subgraph mining to automatically extract temporal trends. We then apply non-negative matrix factorization to group trends in a way that approximates patient pathophysiologic states. Trend groups are then used as features in training a logistic regression model for mortality risk prediction, and are also ranked according to their contribution to mortality risk. We evaluated SANMF against four empirical models on the task of predicting mortality or survival 30 days after discharge from ICU using the observed physiologic measurements between 12 and 24 hours after admission. SANMF outperforms all comparison models, and in particular, demonstrates an improvement in AUC (0.848 vs. 0.827, p<0.002) compared to a state-of-the-art machine learning method that uses manual feature engineering. Feature analysis was performed to illuminate insights and benefits of subgraph groups in mortality risk prediction.
Maximizing Network Topology Lifetime Using Mobile Node Rotation

One of the key challenges facing wireless sensor networks (WSNs) is extending network lifetime due to sensor nodes having limited power supplies. Extending WSN lifetime is complicated because nodes often experience differential power consumption. For example, nodes closer to the sink in a given routing topology transmit more data and thus consume power more rapidly than nodes farther from the sink. Inspired by the huddling behavior of emperor penguins where the penguins take turns on the cold extremities of a penguin “huddle”, we propose mobile node rotation, a new method for using low-cost mobile sensor nodes to address differential power consumption and extend WSN lifetime. Specifically, we propose to rotate the nodes through the high power consumption locations. We propose efficient algorithms for single and multiple rounds of rotations. Our extensive simulations show that mobile node rotation can extend WSN topology lifetime by more than eight times on average which is significantly better than existing alternatives.
A look back at "security problems in the TCP/IP protocol suite

About fifteen years ago, I wrote a paper on security problems in the TCP/IP protocol suite, In particular, I focused on protocol-level issues, rather than implementation flaws. It is instructive to look back at that paper, to see where my focus and my predictions were accurate, where I was wrong, and where dangers have yet to happen. This is a reprint of the original paper, with added commentary.
MouseLight: bimanual interactions on digital paper using a pen and a spatially-aware mobile projector

MouseLight is a spatially-aware standalone mobile projector with the form factor of a mouse that can be used in combination with digital pens on paper. By interacting with the projector and the pen bimanually, users can visualize and modify the virtually augmented contents on top of the paper, and seamlessly transition between virtual and physical information. We present a high fidelity hardware prototype of the system and demonstrate a set of novel interactions specifically tailored to the unique properties of MouseLight. MouseLight differentiates itself from related systems such as PenLight in two aspects. First, MouseLight presents a rich set of bimanual interactions inspired by the ToolGlass interaction metaphor, but applied to physical paper. Secondly, our system explores novel displaced interactions, that take advantage of the independent input and output that is spatially aware of the underneath paper. These properties enable users to issue remote commands such as copy and paste or search. We also report on a preliminary evaluation of the system which produced encouraging observations and feedback.
Thermal Vision for Sleep Apnea Monitoring

The present paper proposes a novel methodology to monitor sleep apnea through thermal imaging. First, the nostril region is segmented and it is tracked over time via a network of cooperating probabilistic trackers. Then, the mean thermal signal of the nostril region, carrying the breathing information, is analyzed through wavelet decomposition. The experimental set included 22 subjects (12 men and 10 women). The sleep-disordered incidents were detected by both thermal and standard polysomnographic methodologies. The high accuracy confirms the validity of the proposed approach, and brings non-obtrusive clinical monitoring of sleep disorders within reach.
Artificial sweeteners induce glucose intolerance by altering the gut microbiota

Non-caloric artificial sweeteners (NAS) are among the most widely used food additives worldwide, regularly consumed by lean and obese individuals alike. NAS consumption is considered safe and beneficial owing to their low caloric content, yet supporting scientific data remain sparse and controversial. Here we demonstrate that consumption of commonly used NAS formulations drives the development of glucose intolerance through induction of compositional and functional alterations to the intestinal microbiota. These NAS-mediated deleterious metabolic effects are abrogated by antibiotic treatment, and are fully transferrable to germ-free mice upon faecal transplantation of microbiota configurations from NAS-consuming mice, or of microbiota anaerobically incubated in the presence of NAS. We identify NAS-altered microbial metabolic pathways that are linked to host susceptibility to metabolic disease, and demonstrate similar NAS-induced dysbiosis and glucose intolerance in healthy human subjects. Collectively, our results link NAS consumption, dysbiosis and metabolic abnormalities, thereby calling for a reassessment of massive NAS usage.
Measures of agreement between computation and experiment: Validation metrics

With the increasing role of computational modeling in engineering design, performance estimation, and safety assessment, improved methods are needed for comparing computational results and experimental measurements. Traditional methods of graphically comparing computational and experimental results, though valuable, are essentially qualitative. Computable measures are needed that can quantitatively compare computational and experimental results over a range of input, or control, variables to sharpen assessment of computational accuracy. This type of measure has been recently referred to as a validation metric. We discuss various features that we believe should be incorporated in a validation metric, as well as features that we believe should be excluded. We develop a new validation metric that is based on the statistical concept of confidence intervals. Using this fundamental concept, we construct two specific metrics: one that requires interpolation of experimental data and one that requires regression (curve fitting) of experimental data. We apply the metrics to three example problems: thermal decomposition of a polyurethane foam, a turbulent buoyant plume of helium, and compressibility effects on the growth rate of a turbulent free-shear layer. We discuss how the present metrics are easily interpretable for assessing computational model accuracy, as well as the impact of experimental measurement uncertainty on the accuracy assessment.
Linear Active Stabilization of Converter-Dominated DC Microgrids

DC microgrids are gaining high momentum under the smart grid environment. DC microgrid stability can be an issue under high penetration of tightly regulated power converters used to interface distributed resources and loads. This paper addresses dc microgrid stability under high penetration of tightly regulated power electronic converters; and proposes three simple and computationally efficient active damping solutions that can be implemented to stabilize a controlled voltage-source converter (VSC) interfacing a dc- microgrid to an ac system. The proposed active damping methods depend on reshaping the VSC impedance by injecting internal-model-based active damping signal at the outer, intermediate and inner control loops of the voltage-oriented VSC interface. Small signal analysis is conducted to assess the system stability under different compensation schemes. Moreover, the reshaped source impedance of the VSC interface and the modified voltage-tracking dynamics are derived under different compensation schemes. Sensitivity and robustness analyses are provided to assess the dynamic coupling among active damping and voltage tracking controllers. Evaluation results, based on a detailed model of a dc microgrid with multiple tightly regulated converter-interfaced loads, are provided to validate the developed models and demonstrate the effectiveness and robustness of proposed techniques.