Miracle-dz/UniFAR-FTUs huggingface dataset:
Kinematic Analysis of the Posterior Cruciate Ligament, Part 1

Background: The posterior cruciate ligament (PCL) is composed of 2 functional bundles and has an essential role in knee function and stability. There is, however, a limited understanding of the role of each individual bundle through the full range of knee flexion. Hypothesis: Both bundles provide restraint to posterior tibial translation across a full range of knee flexion. At higher angles of knee flexion (>90°), the intact PCL also imparts significant rotational stability. Study Design: Controlled laboratory study. Methods: Twenty matched-paired, human cadaveric knees (mean age, 55.2 years; range, 51-59 years; 6 male and 4 female pairs) were used to evaluate the kinematics of an intact, anterolateral bundle (ALB) sectioned, posteromedial bundle (PMB) sectioned, and complete PCL sectioned knee. A 6 degree of freedom robotic system was used to assess knee stability with an applied 134-N posterior tibial load, 5-N·m external and internal rotation torques, 10-N·m valgus and varus torques, and a coupled 100-N posterior tibial load and 5-N external rotation torque at 0°, 15°, 30°, 45°, 60°, 75°, 90°, 105°, and 120°. Results: All sectioned states had significant increases compared with intact in posterior translation, internal rotation, and external rotation at all tested flexion angles, with the exception of the ALB sectioned state at 75° of flexion for external rotation. The significant increases (mean ± standard deviation) in posterior translation during a 134-N posterior tibial load at 90° of flexion were 0.9 ± 0.6 mm, 2.6 ± 1.8 mm, and 11.7 ± 4.0 mm for the PMB, ALB, and complete PCL sectioned states, respectively, compared with the intact state. The largest significant increases in internal rotation were in the PMB and complete PCL sectioned states at 105° of flexion, 1.3° ± 1.0° and 2.8° ± 2.1°, respectively. Conclusion: Both the ALB and the PMB assume a significant role in resisting posterior tibial translation, at all flexion angles, suggesting a codominant relationship. The PCL provided a significant constraint to internal rotation beyond 90° of flexion. Clinical Relevance: This information broadens the understanding of native knee kinematics and provides a template for the evaluation of single- and double-bundle PCL reconstructions.
Approximations of the self-similar solution for blastwave in a medium with power-law density variation

Approximations of the Sedov self-similar solution for a strong point explosion in a medium with the power-law density distribution \rho^o\propto r^{-m} are reviewed and their accuracy are analyzed. Taylor approximation is extended to cases m\neq 0. Two approximations of the solution are presented in the Lagrangian coordinates for spherical, cylindrical and plane geometry. These approximations may be used for the investigation of the ionization structure of the adiabatic flow, i.e., inside adiabatic supernova remnants.
On the Exponentially Weighted Aggregate with the Laplace Prior

In this paper, we study the statistical behaviour of the Exponentially Weighted Aggregate (EWA) in the problem of high-dimensional regression with fixed design. Under the assumption that the underlying regression vector is sparse, it is reasonable to use the Laplace distribution as a prior. The resulting estimator and, specifically, a particular instance of it referred to as the Bayesian lasso, was already used in the statistical literature because of its computational convenience, even though no thorough mathematical analysis of its statistical properties was carried out. The present work fills this gap by establishing sharp oracle inequalities for the EWA with the Laplace prior. These inequalities show that if the temperature parameter is small, the EWA with the Laplace prior satisfies the same type of oracle inequality as the lasso estimator does, as long as the quality of estimation is measured by the prediction loss. Extensions of the proposed methodology to the problem of prediction with low-rank matrices are considered.
Explicit Poincaré equations of motion for general constrained systems. Part II. Applications to multi-body dynamics and nonlinear control

The power of the new equations of motion developed in part I of this paper is illustrated using three examples from multi-body dynamics. The first two examples deal with the problem of accurately controlling the orientation of a rigid body, while the third example deals with the synchronization of two rigid bodies so that their relative orientations are ‘locked’ through prescribed dynamical relationships. The ease, simplicity and accuracy with which control of such highly nonlinear systems is achieved are demonstrated.
Aesthetics in Information Visualization

The importance of visualization in conveying knowledge is undisputed. For example, the rise and fall of stocks is processed and understood faster by examining the corresponding line graph than looking at the raw underlying numbers. For the effectiveness of this cognitive process several factors have been identified in research, like for example the background knowledge, as well as its inherent aesthetics qualities. This text focuses on the latter. It has been argued that the higher the aesthetic value of the visualization is, the more engaged the viewer is in trying to decode its meaning. But what does “aesthetics” mean? Does an informative graphic have to be artistic to be effective? Since the perception of aesthetics is a highly subjective matter, what kind of effort should be put into creating a visualization? What connections between aesthetics and information visualization exist anyway? These questions are the subject of the following text. It starts with an introduction to the relevant terms and subfields of aesthetic information visualization research. It then proceeds with a discussion of several examples of information visualization that were created with a strong aesthetic concern. Since these results often resemble works of art, finally their artistic value is debated.
Gender Inequalities in the Labor Market in Turkey: Differentials in Wages, Industrial & Occupational Distribution of Men and Women

This paper examines gender inequalities in the labor market in Turkey with respect to wage differentials as well as industry- and occupational segregation. We employ standard wage regression estimations as well as the Oaxaca decomposition method to explore the wage differentials between men and women and its underlying causes, namely human capital endowments, occupational and industrial segregation and a series of institutional factors such as private/public sector, coverage of the workplace under a collective labor bargain, social security coverage and firm size. We also examine the extent of gender-based industryand occupational segregation within the confines of our data set and compute the DuncanD and that a sizeable unexplained portion remains due to discriminatory workings of the labor market.
Backward-Slice-Based Statistical Fault Localization without Test Oracles

A recent promising technique for fault localization, Backward-Slice-based Statistical Fault Localization (BSSFL), statistically analyzes the backward slices and results of a set of test cases to evaluate the suspiciousness of a statement being faulty. However, BSSFL like many existing fault localization approaches assumes the existence of a test oracle to determine whether the result of a test case is a failure or pass. In reality, test oracles do not always exist, and therefore in such cases BSSFL can be severely infeasible. Among current research, metamorphic testing has been widely studied as a technique to alleviate the oracle problem. Hence, we leverage metamorphic testing to conduct BSSFL without test oracles. With metamorphic testing, our approach uses the backward slices and the metamorphic result of violation or non-violation for a metamorphic test group, rather than the backward slice and the result of failure or pass for an individual test case in BSSFL. Because our approach does not need the execution result of a test case, it implies that BSSFL can be extended to those application domains where no test oracle exists. The experimental results on 8 programs and 2 groups of the maximal suspiciousness evaluation formulas show that our proposed approach demonstrates the effectiveness comparable to that of existing BSSFL techniques in the cases where test oracles exist.
Synchronous navigation for CT colonography

We present a synchronous navigation module for CT colonography (CTC) reading. The need for such a system arises because most CTC protocols require a patient to be scanned in both supine and prone positions to increase sensitivity in detecting colonic polyps. However, existing clinical practices are limited to reading one scan at a time. Such limitation is due to the fact that building a reference system between scans for the highly flexible colon is a nontrivial task. The conventional centerline approach, generating only the longitudinal distance along the colon, falls short in providing the necessary orientation information to synchronize the virtual navigation cameras in both scanned positions. In this paper we describe a synchronous navigation system by using the teniae coli as anatomical references. Teniae coli are three parallel bands of longitudinal smooth muscle on the surface of the colon. They are morphologically distinguishable and form a piecewise triple helix structure from the appendix to the sigmoid colon. Because of these characteristics, they are ideal references to synchronize virtual cameras in both scanned positions. Our new navigation system consists of two side-by-side virtual colonoscopic view panels (for the supine and prone data sets respectively) and one single camera control unit (which controls both the supine and prone virtual cameras). The capability to examine the same colonic region simultaneously in both scanned images can raise an observer's confidence in polyp identification and potentially improve the performance of CT colonography.
Perceptions of the Safety of the Internet: Fear and the Future of the Web

This paper examines user perception of the risk associated with giving information to online companies, as well as user concerns with personal privacy issues and beliefs that using the Internet can result in personal privacy problems. A proposed research model was created by integrating constructs from previous research, and a survey was conducted to examine one construct from this model, user perception of the Internet or the degree to which individuals discriminate between giving information to online versus traditional companies. Overwhelmingly, respondents report feeling more at risk and less safe when giving information to firms that conduct business only online than when giving information to firms that conduct business only in the traditional face-to-face manner in an office or store. Additionally, nearly two-thirds of those surveyed (sixty-five percent) believe that using the Internet can result in personal privacy problems. Whereas research in this area often points to vendor and/or Web site attributes as dominant factors affecting willingness to give information online, we suggest that positive merchant/Web attributes are necessary but insufficient to provide the assurance of transaction safety that Web users require.
Atechnique for canceling impulse noise in images based on Compressive Sensing

This paper presents a novel technique based on Compressive Sensing (CS) for canceling impulse noise in images. The technique is pivoted around exploiting the strong connection between CS and error correction using the complex (or real) field codes. Even though the usage of real field Bose-Chaudhuri-Hocquenghem (BCH) codes for impulse noise cancellation in images is rather old, bringing the CS framework to address this classical problem in image processing provides a fresh perspective. Specifically, the paper investigates a CS-based product code based on partial Fourier matrices, with the requisite rows chosen based on a Perfect Difference Set (PDS) or consecutively. The decoding algorithms are based on the CS reconstruction and are rather elegant and computationally efficient compared to those considered earlier for real BCH codes. Extensive simulation studies suggest that the novel PDS-based product code is effective in canceling the impulse noise through iterative decoding.
Asymmetric Velocity Distributions from Halo Density Profiles in the Eddington Approach

We show how to obtain the energy distribution f(E) in our vicinity starting from WIMP density profiles in a self-consistent way by employing the Eddington approach and adding reasonable angular momentum dependent terms in the expression of the energy. We then show how we can obtain the velocity dispersions and the asymmetry parameter β in terms of the parameters describing the angular momentum dependence. From this expression, for f(E), we proceed to construct an axially symmetric WIMP a velocity distribution, which, for a gravitationally bound system, automatically has a velocity upper bound and is characterized by the same asymmetriy β. This approach is tested and clarified by constructing analytic expressions in a simple model, with adequate structure. We then show how such velocity distributions can be used in determining the event rates, including modulation, in both the standard and the directional WIMP searches.
Minimize Response Time Using Distance Based Load Balancer Selection Scheme

Cloud computing is one of the concept in virtual technology. Virtualization means that is not real but its provides the all facilities to all different users. Virtualization provides efficient solution in different number of real time applications. Cloud computing is ready to provide the services efficiently to all users. Different numbers of users are submitting the different jobs. All jobs are store into main controller. Main controllers choose the number of load balancers and provide the solution efficiently without any problem. Dynamically choose the number of load balancers and provide the load balancing solution but it takes more time. Static refresh period based updations are available for execution of jobs. Static refresh period time is the insufficient resources for execution [1] [2] [3]. Reduce the time and increase the scalability with the help of distance based load balancers selection. Main controller chooses the neighbor load balancer and allocate the jobs for execution. Once first load balancer goes to overloaded then again main controller takes decision making to allocate the load in next neighbor load balancer. This is the process continue until load balancing results generation. Analyze the situation with dynamic parameters and perform refresh period operation and provides the sufficient solution for execution. It takes less time for providing the response with reduced time delay [3] [2]. keywords: Cloud partitioning technology, main controller, load balancers, cloud computing, virtualization.
Drones in Domestic Surveillance Operations: Fourth Amendment Implications and Legislative Responses

This report first explores the potential uses of drones in the domestic sphere by federal, state, and local governments. It then surveys current Fourth Amendment jurisprudence, including cases surrounding privacy in the home, privacy in public spaces, location tracking, manned aerial surveillance, and those involving the national border. Next, it considers how existing jurisprudence may inform current and proposed drone uses. It then describes the various legislative measures introduced in the 113th Congress to address the legal and policy issues surrounding drones. Finally, it briefly identifies several alternative approaches that may constrain the potential scope of drone surveillance.
Evaluation Strategies for Computational Construction Grammars

Despite the growing number of Computational Construction Grammar implementations, the field is still lacking evaluation methods to compare grammar fragments across different platforms. Moreover, the hand-crafted nature of most grammars requires profiling tools to understand the complex interactions between constructions of different types. This paper presents a number of evaluation measures, partially based on existing measures in the field of semantic parsing, that are especially relevant for reversible grammar formalisms. The measures are tested on a grammar fragment for European Portuguese clitic placement that is currently under development.
Intelligent Agents for the Game of Go

Monte-Carlo Tree Search (MCTS) is a very efficient recent technology for games and planning, particularly in the high-dimensional case, when the number of time steps is moderate and when there is no natural evaluation function. Surprisingly, MCTS makes very little use of learning. In this paper, we present four techniques (ontologies, Bernstein races, Contextual Monte-Carlo and poolRave) for learning agents in Monte-Carlo Tree Search, and experiment them in difficult games and in particular, the Game of Go.
A visual analytics approach to dynamic social networks

The visualization and analysis of dynamic networks have become increasingly important in several fields, for instance sociology or economics. The dynamic and multi-relational nature of this data poses the challenge of understanding both its topological structure and how it changes over time. In this paper we propose a visual analytics approach for analyzing dynamic networks that integrates: a dynamic layout with user-controlled trade-off between stability and consistency; three temporal views based on different combinations of node-link diagrams (layer superimposition, layer juxtaposition, and two-and-a-half-dimensional view); the visualization of social network analysis metrics; and specific interaction techniques for tracking node trajectories and node connectivity over time. This integration of visual, interactive, and automatic methods supports the multi-faceted analysis of dynamically changing networks.
Tamper-Resistant Execution in an Untrusted Operating System Using A Virtual Machine Monitor

Software applications today face constant threat of tampering because of the vulnerability in operating systems and their permissive interface. Unfortunately, existing tamper-resistance approaches often require non-trivial amount of changes to core CPU architectures, operating systems and/or applications. In this paper, we propose an approach that requires only minimal changes to existing commodity operating systems running on commodity hardware without compromising their functionality and compatibility. The key idea is to use a trustworthy virtual machine monitor (VMM) to monitor and regulate the behavior of other untrustworthy processes including the underlying operating system that might have been compromised. We use the trusted VMM to compartmentalize a process that demands tamper resistant protection from OS kernels and other processes, by interposing security-sensitive operations (e.g. system calls) and isolating (and sealing) security-sensitive information (e.g. registers and memory). We have implemented a working prototype, CHAOS 1 , that supports tamper-resistant applications running on Linux and Xen VMM. Our prototype shows that it only requires minor changes (about 230 LOCs) to Linux and a small amount of code expansion to Xen (about 4200 LOCs). Performance measurements also show that CHAOS incurs a little performance degradation to the application software: about 3% for SPECINT-2000 and less than 15% for apache httpd and vsftpd.
A reinforcement learning approach for and scheduling packets in dynamic networks

Actually, various kinds of sources (such as voice, video, or data) with diverse traffic characteristics and quality of service requirements (QoS), which are multiplexed at very high rates, leads to significant traffic problems such as packet losses, transmission delays, delay variations, etc, caused mainly by congestion in the networks. The prediction of these problems in real time is quite difficult, making the effectiveness of "traditional" methodologies based on analytical models questionable. Effective network routing means selecting the optimal communication paths. It can be modeled as a multiagent RL problem. We propose an adaptive routing and scheduling algorithm based on reinforcement learning techniques.
Patenting and industrial performance: the case of the machine tool industry

Am Beispiel einer wichtigen Investitionsguterindustrie wird in diesem Beitrag der Einflus nationaler Patentsysteme auf den Unternehmenserfolg untersucht. Zahlreiche Theorien gehen davon aus, das das Innovationsverhalten von Unternehmen von nationalen und sektoralen Innovationssystemen beeinflust wird. Das Patentrecht spielt in diesen Systemen eine wichtige Rolle. Auf der Unternehmensebene beeinflust es die Moglichkeiten der Unternehmen Gewinne zu erzielen. Am Beispiel der 49 grosten Unternehmen der internationalen Werkzeugmaschinenindustrie wird nachgewiesen, das in diesem Industriezweig Patente ein wichtiges Instrument zur Erzielung von Gewinnen darstellen. Dies zeigt sich besonders deutlich an der engen positiven Beziehung, die zwischen dem Marktwert der Unternehmen und ihrem Patentierverhalten empirisch festgestellt wurde.
Polymyxin B Resistance in El Tor Vibrio cholerae Requires Lipid Acylation Catalyzed by MsbB

ABSTRACT Antimicrobial peptides are critical for innate antibacterial defense. Both Gram-negative and Gram-positive microbes have mechanisms to alter their surfaces and resist killing by antimicrobial peptides. In Vibrio cholerae, two natural epidemic biotypes, classical and El Tor, exhibit distinct phenotypes with respect to sensitivity to the peptide antibiotic polymyxin B: classical strains are sensitive and El Tor strains are relatively resistant. We carried out mutant screens of both biotypes, aiming to identify classical V. cholerae mutants resistant to polymyxin B and El Tor V. cholerae mutants sensitive to polymyxin B. Insertions in a gene annotated msbB (encoding a predicted lipid A secondary acyltransferase) answered both screens, implicating its activity in antimicrobial peptide resistance of V. cholerae. Analysis of a defined mutation in the El Tor biotype demonstrated that msbB is required for resistance to all antimicrobial peptides tested. Mutation of msbB in a classical strain resulted in reduced resistance to several antimicrobial peptides but in no significant change in resistance to polymyxin B. msbB mutants of both biotypes showed decreased colonization of infant mice, with a more pronounced defect observed for the El Tor mutant. Mass spectrometry analysis showed that lipid A of the msbB mutant for both biotypes was underacylated compared to lipid A of the wild-type isolates, confirming that MsbB is a functional acyltransferase in V. cholerae.
Homotopy Parametric Simplex Method for Sparse Learning

High dimensional sparse learning has imposed a great computational challenge to large scale data analysis. In this paper, we are interested in a broad class of sparse learning approaches formulated as linear programs parametrized by a {\em regularization factor}, and solve them by the parametric simplex method (PSM). Our parametric simplex method offers significant advantages over other competing methods: (1) PSM naturally obtains the complete solution path for all values of the regularization parameter; (2) PSM provides a high precision dual certificate stopping criterion; (3) PSM yields sparse solutions through very few iterations, and the solution sparsity significantly reduces the computational cost per iteration. Particularly, we demonstrate the superiority of PSM over various sparse learning approaches, including Dantzig selector for sparse linear regression, LAD-Lasso for sparse robust linear regression, CLIME for sparse precision matrix estimation, sparse differential network estimation, and sparse Linear Programming Discriminant (LPD) analysis. We then provide sufficient conditions under which PSM always outputs sparse solutions such that its computational performance can be significantly boosted. Thorough numerical experiments are provided to demonstrate the outstanding performance of the PSM method.