Miracle-dz/UniFAR-FTUs huggingface dataset:
Cardinal Pill Testing of System Virtual Machines

Malware analysis relies heavily on the use of virtual machines for functionality and safety. There are subtle differences in operation between virtual machines and physical machines. Contemporary malware checks for these differences to detect that it is being run in a virtual machine, and modifies its behavior to thwart being analyzed by the defenders. Existing approaches to uncover these differences use randomized testing, or malware analysis, and cannot guarantee completeness. In this paper we propose Cardinal Pill Testing--a modification of Red Pill Testing [21] that aims to enumerate the differences between a given VM and a physical machine, through carefully designed tests. Cardinal Pill Testing finds five times more pills by running fifteen times fewer tests than Red Pill Testing. We further examine the causes of pills and find that, while the majority of them stem from the failure of virtual machines to follow CPU design specifications, a significant number stem from under-specification of the effects of certain instructions by the Intel manual. This leads to divergent implementations in different CPU and virtual machine architectures. Cardinal Pill Testing successfully enumerates differences that stem from the first cause, but only exhaustive testing or an understanding of implementation semantics can enumerate those that stem from the second cause. Finally, we sketch a method to hide pills from malware by systematically correcting their outputs in the virtual machine.
Security Pre-screening of Moving Persons Using a Rotating Multichannel $W$ -Band Radar

This contribution describes a novel millimeter-wave radar system for security checks of persons. The goal of the system is not the classical airport checkpoint situation, but it should support existing security systems by a fast and effective prescreening of moving persons to identify threats in an early stage. With the proposed experimental system, exceptionally dangerous objects can be detected and localized on the body of moving persons. The radar operates in the band between 96 and 99 GHz and consists of one transmit and five coherent receive channels. The transmit and receive modules are fabricated in split-block technology using 100-nm metamorphic HEMT MMICs processed at Fraunhofer IAF.
Effects of slaughter age on meat tenderness and USDA carcass maturity scores of beef females.

Two experiments were conducted to determine the effect of carcass maturity on meat palatability using concentrate-fed cattle of known history and to determine the relationship of chronological age to carcass maturity scores. Yearling heifers (n = 28) and 2-yr-old cows (n = 25) of similar breed groups were fed a high-energy-density diet for 90 d before slaughter. Longissimus muscle Instron peak load (Warner-Bratzler shear force) did not differ between age groups; but, fail elongation was higher for the 2-yr-old cows (P < .05). Overall tenderness ratings were lower for the 2-yr-old cows; however, the magnitude of the tenderness difference between age groups was small (.4 units on an 8-point scale). There was 10-fold more variation in tenderness within each age group than there was between age groups. Carcass maturity scores and chronological age were compared for heifers and cows (n = 249) ranging in age from 1.7 to 13.9 yr. Carcass maturity scores increased with increasing chronological age at a much faster rate than indicated by USDA. The following chronological age groups most accurately reflected the chronological age associated with each USDA carcass maturity class: A, 9 to 24 mo; B, 24 to 36 mo; C, 36 to 48 mo; D, 48 to 60 mo; E, > 60 mo. These results indicate that efforts to control variation in tenderness would be more effective if they targeted factors that have a greater effect on meat tenderness than does maturity class. Moreover, our results indicate that cows may grade lower at a given age than what USDA standards imply.
How good are your phrases? Assessing phrase quality with single class classification

We present a novel translation quality informed procedure for both extraction and scoring of phrase pairs in PBSMT systems. We reformulate the extraction problem in the supervised learning framework in an attempt to take into account the translation quality, while incorporating arbitrary features in order to circumvent alignment errors. One-Class SVMs and the Mapping Convergence algorithm permit training a single-class classifier to discriminate between useful and useless phrase pairs, by learning from a training corpus that comprises only useful instances. Employing confidence scores, produced by the classifier as a selection criteria, allows a fine control over the size of the resulting translation model, while providing at the same time a new accuracy-based feature to score phrase pairs. Experimental evaluation of the method shows accurate assessments of phrase pairs quality even for regions in the space of possible phrase pairs that are ignored by other approaches, which leads to improvements in translation performance as measured by BLEU.
Stereological estimation for layered structures based on slabs perpendicular to a surface

This paper deals with the characterization of layered structures sampled with respect to a reference surface. A scheme where thick slabs are sampled perpendicular to a curved surface is considered, resulting in a non‐uniform sampling of the structure. We present an estimation procedure based on the Horvitz–Thompson principle. An approximation of the sampling probability is proposed, which depends on the local surface curvatures, on the slab dimensions and on the intensity function of slab anchors. The practical determination of local parameters is detailed for the case of a revolution surface. The procedure is applied to the estimation of surface area density of cell walls in tomato pericarp.
Intensity Modulated Radiotherapy ( IMRT ) for Central Nervous System ( CNS ) Tumors Effective : October 1 , 201 8

PLEASE NOTE: Contracts exclude from coverage, among other things, services or procedures that are considered investigational or cosmetic. Providers may bill members for services or procedures that are considered investigational or cosmetic. Providers are encouraged to inform members before rendering such services that the members are likely to be financially responsible for the cost of these services.
Learning Rules from Incomplete Examples: A Pragmatic Approach

In this paper, we consider the problem of inductively learning rules from specific facts extracted from texts. This problem is challenging due to two reasons. First, natural texts are radically incomplete since there are always too many facts to mention. Second, natural texts are systematically biased towards novelty and surprise, which presents an unrepresentative sample to the learner. Our solutions to these two problems are based on building a generative observation model of what is mentioned and what is extracted given what is true. We first present a Multiple-predicate Bootstrapping approach that consists of iteratively learning if-then rules based on an implicit observation model and then imputing new facts implied by the learned rules. Second, we present an iterative ensemble colearning approach, where multiple decision-trees are learned from bootstrap samples of the incomplete training data, and facts are imputed based on weighted majority.
Cost of Production and Price over Long and Short Periods

Great difficulties are met with in stating a clear and straightforward exposition of price theory because of the fact that the given conditions or data of the problem are so different according to the length of the time period which the explanation takes into account. The forces which immediately regulate prices are different from those which ultimately control, and there are degrees or stages in both immediateness and ultimateness. The average student of economics is likely to be quite baffled by these distinctions and to get no clear ideas at all; but he is still more baffled by differences in degree, where distinctions are not sharply drawn and statements are left in the form of "it depends. " This paper looks to the problem of exposition from the standpoint of the student rather than to the correction of errors in accepted doctrine, but the course of the argument will have to note cases in which current phraseology is misleading to unwary readers if it does not represent fundamental misconceptions on the part of economists themselves.
The influence of accelerating the setting rate by ultrasound or heat on the bond strength of glass ionomers used as orthodontic bracket cements

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Building a digital application for teaching vital signs.

OBJECTIVE To describe the steps in creating a digital application directed to teaching vital signs for nursing students. METHOD This is a methodological study, conducted from March to October 2014, in which have followed the stages of analysis, design and development of technological tool, based on the theoretical framework of Galvis-Panqueva. We conducted a narrative review of the literature on the subject, and then picked up the best platform for application hosting. RESULTS Once the steps proposed in the theoretical framework were followed, the analysis outlined the content and technological infrastructure. As for the design, it provided the assessment of the environment and its interface and operation, and finally the development materialized the projection of the design and interactive features proposed in previous steps. CONCLUSION The application is an interactive support in the training of nursing students, and it is suggested that validation of content be performed for further practical application.
FeaFiner: biomarker identification from medical data through feature generalization and selection

Traditionally, feature construction and feature selection are two important but separate processes in data mining. However, many real world applications require an integrated approach for creating, refining and selecting features. To address this problem, we propose FeaFiner (short for Feature Refiner), an efficient formulation that simultaneously generalizes low-level features into higher level concepts and then selects relevant concepts based on the target variable. Specifically, we formulate a double sparsity optimization problem that identifies groups in the low-level features, generalizes higher level features using the groups and performs feature selection. Since in many clinical researches non- overlapping groups are preferred for better interpretability, we further improve the formulation to generalize features using mutually exclusive feature groups. The proposed formulation is challenging to solve due to the orthogonality constraints, non-convexity objective and non-smoothness penal- ties. We apply a recently developed augmented Lagrangian method to solve this formulation in which each subproblem is solved by a non-monotone spectral projected gradient method. Our numerical experiments show that this approach is computationally efficient and also capable of producing solutions of high quality. We also present a generalization bound showing the consistency and the asymptotic behavior of the learning process of our proposed formulation. Finally, the proposed FeaFiner method is validated on Alzheimer's Disease Neuroimaging Initiative dataset, where low-level biomarkers are automatically generalized into robust higher level concepts which are then selected for predicting the disease status measured by Mini Mental State Examination and Alzheimer's Disease Assessment Scale cognitive subscore. Compared to existing predictive modeling methods, FeaFiner provides intuitive and robust feature concepts and competitive predictive accuracy.
FEEDBACK CONTROL ANALYSIS OF A STEREO ACTIVE VISION SYSTEM

The position and orientation estimation of a stereo camera system is of key importance in 3D scene reconstruction. In this paper, the authors present a feedback analysis of an active vision system used to control the pan, tilt and zoom of an active stereo camera. The proposed procedure considered both a time and frequency domain analysis. The main outcome of the research presented here is the analytical computation of the maximum dead-time value which the vision system can introduce.
Between BRIC and G 3 : Shariah-Compliant Stock Markets Cointegration

This study aims to examine the persistence of Shariah-compliant stock markets cointegration between the BRIC (Brazil, Russia, India and China) and the G3 (US, Europe and Japan). The analysis utilises monthly data of seven S&P Shariah Dow Jones Indices to represent Shariah-compliant stock markets in the BRIC and in the G3, covering the period of November 2007 to August 2013. The method incorporated is autoregressive distributed lag (ARDL) model. It evidenced that each of the Shariah-compliant stock market in the BRIC countries is not cointegrated with their counterparts in the G3. This finding could cater Islamic-oriented investors and asset managers in the G3 countries significant risk reduction in their portfolio diversification for a given level of return for investing in one of the Shariahcompliant stock market in the BRIC countries.
SEASONAL WEED STRUCTURE OF MAIZE IN THE LIGHT OF FARMING SYSTEMS

The differences between the cultivation of conventional and organic fields can result in changes in weed flora. Although herbicides do not affect all weed species equally, their use can have long-term effects on weeds and may prevent their emergence for weeks after treatment. On the other hand, the common mechanical weed control of organic farms is not selective, but weeds can reappear immediately after the treatment. Nonchemical techniques of weed control are not only used under organic conditions, but also in conventional fields, because of the increasing demands for the restricted use of chemicals in food production. The main aim of our research is to see how different weed control practices result in different weed populations, and how these populations change during the growing season of maize. This work was based on data from 93 conventional and organic maize fields in south-eastern Hungary surveyed between 2007 and 2011. The studied fields were divided into four groups, according to the farming system employed and the season of the survey (conventional in spring, conventional in summer, organic in spring, organic in summer). The aim was to explore the seasonal change of weed flora and the differences between farming systems. Our analysis, which included a comparison of the main weed species, shows that fields managed conventionally and organically are different in terms of both their early and late vegetation. Conventional fields in spring were the most distinct from the other three field groups, as they were not well characterized by any weed species. All the other field groups had dominant species present.
Individual Entrepreneurial Exit and Earnings in Subsequent Paid Employment

We study earnings of individuals who exit entrepreneurship for paid employment. We find mean (median) positive rewards from entrepreneurship in subsequent paid employment relative to matched employees. Rewards are higher for former entrepreneurs hired in highly innovative sectors. We also find that the performance of the exited firm is a strong predictor of the earnings premium for former entrepreneurs when the firm performed well, while we do not find median discounts for entrepreneurs exiting low performing firms. We use registry data that encompass the population of firms and individuals in the Norwegian economy.
USE OF EPORTFOLIOS IN K-12 TEACHER HIRING IN NORTH CAROLINA: PERSPECTIVES OF SCHOOL PRINCIPALS

This study explored the perceptions of principals involved in the hiring process of K–12 teachers in 11 counties in southeastern North Carolina. Forty-nine principals responded to a survey on ePortfolio use in the hiring process: the pros and cons, desirable artifacts, stage of use, preferred delivery method, and improvements that can increase their usage. We examined each of these questions and whether certain factors (prior use, technology skills, and years as a hiring agent) predict principals' ePortfolio use. Our findings suggest that ePortfolios provide improved and current information about teacher candidates that is easily accessible and organized. Collectively, this allows principals to assess teacher candidates’ suitability for employment. Although, there are problems associated with ePortfolio use during hiring, which are detailed below, the results suggest that principals most frequently use ePortfolios during the interview process, prefer delivery via a website address, and that prior use is the best predictor of future ePortfolio use.
WebPropagate : A Web Server for Network

Network propagation is a powerful tool for genetic analysis which is widely used to identify genes and genetic modules that underlie a process of interest. Here we provide a graphical, web-based platform (http://anat.cs. tau.ac.il/WebPropagate/) in which researchers can easily apply variants of this method to data sets of interest using up-to-date networks of protein–protein interactions in several organisms. © 2018 Elsevier Ltd. All rights reserved.
Genre Classification based on Predominant Melodic Pitch Contours

We present an automatic genre classification system based on melodic features. First a ground truth genre dataset composed of polyphonic music excerpts is compiled. Predominant melodic pitch contours are then estimated, from which a series of descriptors is extracted. These features are related to melody pitch, variation and expressiveness (e.g. vibrato characteristics, pitch distributions, contour shape classes). We compare different standard classification algorithms to automatically classify genre using the extracted features. Finally, the model is evaluated and refined, and a working prototype is implemented. The results show that the set of melody descriptors developed is robust and reliable. They also reveal that complementing low level timbre features with high level melody features is a promising direction for genre classification. ii iii Acknowledgements
SIW Rotman Lens with Planar Slot Array Antenna at Ku-band

─ A multi-beam antenna, which is the combination of a Rotman lens and a planar slot array antenna, is designed in this paper. The lens and the slot array are designed for 15.5 to 16.5 GHz frequency range and implemented in the same substrate using SIW structure. The Rotman lens with 7 input ports and 7 output ports are connected to a planar slotted array antenna with 7 waveguides. This multi-beam antenna consists of seven beams at angles of 0°, ±10°, ±20° and ±30° symmetrically. This antenna is designed for terrestrial and satellite applications, where the low cost, low profile and light multi-beam antennas are needed. Simulated and measured results show that the amplitude and phase distributions and scattering parameters of the antenna are in good agreement. In addition, the SLL, HPBW, main beam direction and cross polarization levels of all the radiation patterns are desirable. Index Terms ─ Beam steering, Rotman lens, slot array antenna, Substrate Integrated Waveguide (SIW).
A business process metamodel for Enterprise Information Systems automatic generation

Business Processes Modeling (BPM) is a critical success factor for Enterprise Information Systems (EIS), since a process represents the know-how accumulated by the organization and improves the productivity of its members. Model-Driven Development (MDD) approaches are being increasingly applied to generate Information Systems software, but current proposals have failed in observing BPM aspects and, therefore, they do not support many requirements of business processes execution and management. This paper proposes a business process metamodel to assist MDD initiatives in providing such capabilities to the generated Information System software. The proposed metamodel adapts and extends the BPMN [OMG 2009] concepts in order to build the modeling primitives to MDD initiatives. This metamodel was applied to improve an existing MDD framework that generates and manages code for EIS.
Surplus Consumption Ratio Estimated Using Market Prices Vs Consumption Data

I use index prices and options to estimate the pricing kernel’s elasticity, which approximates the fundamental component of Campbell and Cochrane (1999), the surplus consumption ratio. The approximation relies on an empirically motivated, time-varying relationship between consumption growth and the expected returns on market wealth, therefore avoiding problematic consumption data. I show that my estimate of the surplus consumption ratio: predicts future excess market returns, is highly correlated to business cycle variables and the SVIX of Martin (2017), and is priced in a cross-sectional analysis of equity returns. The results provide new empirical support for consumption-based asset pricing models.
Implementing a Class of Permutation Tests: The coin Package

The R package coin implements a unified approach to permutation tests providing a huge class of independence tests for nominal, ordered, numeric, and censored data as well as multivariate data at mixed scales. Based on a rich and flexible conceptual framework that embeds different permutation test procedures into a common theory, a computational framework is established in coin that likewise embeds the corresponding R functionality in a common S4 class structure with associated generic functions. As a consequence, the computational tools in coin inherit the flexibility of the underlying theory and conditional inference functions for important special cases can be set up easily. Conditional versions of classical tests---such as tests for location and scale problems in two or more samples, independence in two- or three-way contingency tables, or association problems for censored, ordered categorical or multivariate data---can easily be implemented as special cases using this computational toolbox by choosing appropriate transformations of the observations. The paper gives a detailed exposition of both the internal structure of the package and the provided user interfaces along with examples on how to extend the implemented functionality.
P o S ( L H C P 2 0 1 8 ) 0 0 5 Search for tt̄H production in high-p T regimes with the ATLAS detector

The associated production of the Higgs boson with a pair of top/anti-top quarks (tt̄H) is the only process providing the direct access to the measurement of the Yukawa coupling between the Higgs boson and the top quark. The presented results exploit the data collected during 2015 and 2016 by the ATLAS experiment during LHC collisions at a center-of-mass energy of 13 TeV. Multivariate analysis techniques are used in order to discriminate the signal from the very large backgrounds arising mainly from top-quark pair production. In addition, for the first time the analysis uses algorithms specifically designed to cope with the challenging reconstruction of hadronically decaying high-pT bosons and top quarks. The combined best fit value of the signal strength is found to be 0.84+0.64 −0.61, while a value greater than 2.0 is excluded at 95% confidence level while the expected upper limit is μ < 1.2 in the absence of a tt̄H signal.