Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel-Coordinates Art

We employ common information visualization techniques such as parallel coordinates or stardinates as a tool for artistic image generation. Our technique is based on rendering footprints of continuous density distributions as they emerge from modeling data with uncertainty or estimating probability densities. By compositing density footprints with alpha-blending, we obtain visually pleasing images from high-dimensional input data. We further give examples of a number of controls that can be used to tailor the outcome of the algorithm.
Association between HLA-B*46 Allele and Graves Disease in Asian Populations: A Meta-Analysis

Graves' disease (GD) is a leading cause of hyperthyroidism, which affects 1.0-1.6% of the general population. Previous studies reported a higher GD prevalence in Asian populations compared to Caucasian populations. The etiology of GD involves complex interactions between predisposing genes and environmental triggers. Genetic studies have shown that the human leukocyte antigen (HLA) is an important candidate genetic region associated with GD in Asian populations. However, the results were inconsistent and inconclusive. Here, we performed a meta-analysis to evaluate the role of the HLA-B*46 allele in GD in Asian populations. A total of 14 case-controlled studies on the association of the HLA-B*46 allele in 1743 GD patients and 5689 controls were included. Our results showed a trend toward an increased risk of GD in HLA-B*46-positive subjects compared to those HLA-B*46-negative (OR = 2.48; 95% CI = 1.96-3.13, P < 0.01). However, there were some limitations to the current meta-analysis, such as heterogeneity (Pheterogeneity < 0.01 and I2 = 68.0%) or the different typing methods (serological and genotyping methods). The meta-analysis indicated that the HLA-B*46 allele is a risk factor for GD in Asian populations. Future studies on the role of the HLA-B*46 allele in GD should consider complications such as periodic paralysis, ophthalmopathy and recurrence.
Predicting drug metabolism: Concepts and challenges

Abstract The paper begins with a discussion of the needs and goals of metabolic predictions in early drug research. Major difficulties toward this objective are examined, mainly the various substrate and product selectivities characteristic of drug metabolism. In a second part, we classify and summarize the major in silico methods used to predict drug metabolism. A discrimination is thus made between “local ”and “global ”systems. In the last part of the paper, the program METEOR is presented and evaluated using the published metabolic data of 10 substrates.
A linear MPC algorithm for embedded systems with computational complexity guarantees

In this paper we propose a linear MPC scheme for embedded systems based on the dual fast gradient algorithm for solving the corresponding control problem. We establish computational complexity guarantees for the MPC scheme by appropriately deriving tight convergence estimates of order O(1/k2) for an average primal sequence generated by our proposed numerical optimization algorithm. We also show that these estimates rely heavily upon the dual optimal variables (Lagrange multipliers). Since convergence certification in embedded MPC is essential, we also derive tight bounds on the norm of these dual optimal variables. However, computing the norm for the Lagrange multipliers associated to multi-parametric optimization problems can quickly become intractable for high dimension and/or a large set of constraints. Therefore, we recast the problem in a mixed integer formulation by using auxiliary binary variables to characterize the complementarity conditions. We also show that this problem can be solved numerically efficiently.
Rigidity for Anosov Actions of Higher Rank Lattices

This is the simplest example of a large class of analytic "standard" actions of lattices in semisimple Lie groups on locally homogeneous spaces. A basic problem is to understand the differentiable actions near to such a standard action in terms of their geometry and dynamics (cf. [13], [50], [51]). A Cr-action So: IF > X -x X of a group F on a compact manifold X is said to be Anosov if there exists at least one element, Yh E F, such that 'p(Yh) is an Anosov diffeomorphism of X. We begin in this paper to study the Anosov differentiable actions of lattices, including many standard algebraic examples, and especially to study their stability properties. Our main theme is that either the Cr-rigidity or the Cr-deformation rigidity of an Anosov action (for 1 < r < cr. or even for the real analytic case) can be shown just by studying the behavior of the periodic orbits for the action. There are two notions of "structural stability" that appear in this paper, rigidity and deformation rigidity. A Cl-perturbation of a Cr-action So is simply another Cr-action Spl such that for a finite set of generators {81, . , ad of F, the Cr-diffeomorphisms 'P(8i) and 'Pl(8i) are Cl-close for all i. An action So is said to be Cr-rigid (or topologically rigid if r = 0) if every sufficiently small C'perturbation of So is Cr-conjugate to So, for 0 < r < oo, or r = w in the case of real analytic actions. A Cl-deformation of an action So is a continuous path of Cr-actions (Pt defined for some 0 < t < e with Spo = SD* An action SD is said to be Cr-deform-
CANONICAL FORM AND SEPARABILITY OF PPT STATES ON MULTIPLE QUANTUM SPACES

By using the "subtracting projectors" method in proving the separability of PPT states on multiple quantum spaces, we derive a canonical form of PPT states in $\mathbb{C}^{K_1}\otimes \mathbb{C}^{K_2}\otimes \cdots \otimes \mathbb{C}^{K_m}\otimes \mathbb{C}^N$ composite quantum systems with rank N, from which a sufficient separability condition for these states is presented.
Adaptation of the GreenLab Model for Analyzing Sink-Source Relationships in Chinese Pine Saplings

Since the 1990s, a new generation of models has emerged to simulate tree growth with consideration of both tree structure and functional processes. However, calibration of these functional-structural models (FSMs) often remains an open problem due to the topological complexity of trees and to the heavy measurements required. In this paper, we explore a possible way for dealing with the fitting problem, based on the GreenLab model approach. Detailed organ-level data including topological and geometrical measurements were collected on eight Chinese Pine (Pinus tabulaeformis Carr.) saplings grown near Beijing. Adaptation of GreenLab to introduce a flexible modeling for biomass allocation to ring growth is presented. The main assumptions, such as allometry rules and sink relationships, were investigated. The problem of calibration of a complex branching structure was solved by defining an average tree. The results were interpreted with particular focus on the ones concerning the hidden mechanisms of secondary growth.
Spatial Probing of Traps in nMOSFET with ALD HfO2/SiO2 Stacks Using Low Frequency Noise Characteristics

Low frequency (LF) noise is studied in n-type metal-oxide-semiconductor field-effect-transistors (nMOSFETs) with various HfO2 or interfacial layer (IL) thicknesses and is found to be dominated by 1/f noise in the frequency range 1 Hz lesfles 1.6 kHz. LF noise magnitude increases with HfO2 thickness and decreases with IL SiO2 thickness. Traps at the channel and dielectric interface do not contribute to the 1/f noise or cannot be resolved from thermal noise. The LF noise correlates well with the hysteresis or Vth instability observed during DC measurements. The volume trap density calculated from 1/f noise analysis is more than one order of magnitude higher in 7 nm HfO2 than in 3 nm HfO2 devices. Qualitative trap spatial profiles can be obtained from the LF spectra, and the stress induced redistribution of trap distribution is discussed
Experiences and lessons from the analysis of TCAS II

This report highlights some of the experiences gathered while analyzing the requirements specification for a commercial avionics system called TCAS II (Traffic alert and Collision Avoidance System II) for consistency and completeness. Completeness in this context is defined as a complete set of requirements, that is, there is a behavior specified for every possible input and input sequence.Under the leadership of Dr. Nancy G. Leveson, the Irvine Safety Research Group has developed a state-based requirements specification language RSML (Requirements State Machine Language) using TCAS II as a testbed [6]. The TCAS requirements specification project was very successful; RSML was well liked by all participants in the project, and the formal specification has been adopted as the official TCAS II requirements. The requirements document has been delivered to the FAA and has undergone an extensive independent validation and verification effort (IV&amp;V). In a previous investigation, we defined procedures for analyzing state-based requirements specifications for completeness and consistency [5]. To demonstrate that our approach is feasible and is applicable to realistic systems, we have implemented a draft analysis tool and we have applied the analysis to the TCAS II requirements. The initial results from the analysis effort were encouraging [4, 5] and scaled well to a large requirements specification. The most complex parts of the TCAS requirements specification have recently been analyzed. Even though the effort was largely successful, some limitations with the approach have surfaced. Most importantly, the accuracy of the analysis algorithms needs improvement. When analyzing the most complex parts of the TCAS requirements, the number of spurious error reports can occasionally be overwhelming. Furthermore, we discovered that once the analysis has identified problems, it has been unexpectedly difficult to correct some of them.
Main Memory DBMS on Modern Processors , a Simulation Approach for Database Performance Characterization

Database applications are an important type of workloads th at is very different from other types of application workloads such as SPEC benchmarks. In the past, much research has been devoted to evaluate performance characteristics of database workloads on vari ous processor architectures. While most of the previous performance evaluations have been done using hard ware counters, many recently developed fullsystem simulators have provided another method for perform ance characterization. With the simulation paradigm, some architectural features of processors that w ere hard to examine using hardware counters are now accessible. However, results of simulations have to be validated against real machine executions to ensure their fidelity. In this paper, we extend the Simics f ull-system simulator to measure performance of architectural features of a simulated Pentium 4 alike PC r unning TPC-H workload on MonetDB (a main memory database management system). Then, we compare o ur simulation results with some wellestablished results published in literature previously. O ur contributions are: (i) a flexible simulation methodology to characterize database performance; (ii) a c lose study of TPC-H benchmark performance including bandwidth measurement between memory and CPU, wh ich has not been revealed in previously published research; (iii) validation of the simulation res ult against real machine measurement. Specifically, we find that our simulation results are mostly consistent wit h previously published results. In our simulation, approximately 83% of query execution time in th e database is spent on various stalls. Memory stalls and resource-related stalls are the most prominent o nes for all TPC-H queries under test.
Acute Response Of Bone Metabolism To Various Resistance Exercises In Women

Abstract The study examines the acute response of bone turnover markers to two different single bouts of resistance exercises in women. Serum bone alkaline phosphatase and sclerostin concentration were measured before, 24 and 48 hours after the interventions to detect the dynamics of bone turnover. Subjects performed two exercises and a control experiment without exercise (CONTR) on different occasions, with 3-week breaks between the interventions, in a random order. First exercises protocol had a constant resistance of 75 % 1 RM (ISOF). Second, serial stretch loading (SSL), was isokinetic: velocity of concentric and eccentric phase of the movement was 50 and 40 cm/s, respectively. Short stops were incorporated into both phases of the movement after every 20 mm, resulting in a frequency of the force peaks of 10 Hz in concentric as well as in eccentric phase. Both protocols consisted of 6 sets of 6 repetitions and 2-minute resting periods. The exercises interventions had no statistically significant effect on either bone turnover marker concentration at any of the time points.
Assessment of Health-Related Quality of Life: The Cinderella of Peritoneal Dialysis?

The studies of quality of life (QoL) are becoming increasingly interesting in clinical setting because their findings have implications for making decisions on resource allocation and health policies. The assessment of health-related QoL is especially directed to patients with chronic illnesses that cause progressive deterioration and limitations, and consume the bulk of financial resources for health. Among these chronic kidney disease and, more specifically the renal replacement therapy, is an important condition. Due to the diagnostic and therapeutic advances, we see a gradual increase both in the number of the dialysis population and its age, which leads to a growing interest in the study of these patients' QoL, as evidenced by more than one thousand articles published on this subject.
Future Link Prediction in the Blogosphere for Recommendation

The phenomenal growth in both scale and importance of social media such as blogs, micro-blogs and user-generated content, has created a need for tools that monitor information diffusion and make recommendations within these platforms. An essential element of social media, particularly blogs, is the hyperlink graph that connects various pieces of content. There are two types of links within the blogosphere; one from blog post to blog post, and another from blog post to blog channel (an event stream of blog posts). These links can be viewed as a proxy for the flow of information between blog channels and to reflect influence. Given this assumption about links, the ability to predict future links can facilitate the monitoring of information diffusion, making recommendations, and word-of-mouth (WOM) marketing. We propose different methods for link predictions and we evaluate these methods on an extensive blog dataset.
OPA 1-dependent cristae morphogenesis in mitochondria Prohibitins control cell proliferation and apoptosis by regulating data

data Supplementary http://genesdev.cshlp. org/cgi/content/full/22/4/476/DC1 "Supplemental Research Data" References http://genesdev.cshlp. org/cgi/content/full/22/4/476#References This article cites 60 articles, 25 of which can be accessed free at: service Email alerting click here top right corner of the article or Receive free email alerts when new articles cite this article sign up in the box at the
Using LEGO NXT Mobile Robots With LabVIEW for Undergraduate Courses on Mechatronics

The paper proposes lab work and student competitions based on the LEGO NXT Mindstorms kits and standard LabVIEW. The goal of this combination is to stimulate design and experimentation with real hardware and representative software in courses where mobile robotics is adopted as a motivating platform to introduce mechatronics competencies. Basic LabVIEW examples are proposed for three case-study laboratory practices. These are implemented with the NXT Toolkit and the NXT Direct Command programming libraries for standalone and remote execution, respectively. The application of this instructional material has been tested in two different experiences with senior undergraduate engineering students. A description of the courses as well as an assessment of student results are also included.
Optical orthogonal codes: Design, . . .

Ahstruct-An optical orthogonal code is a family of (0,l) sequences with good auto-and cross-correlation properties, i.e., the autocorrelation of each sequence exhibits the " thumbtack " shape and the cross correlation between any two sequences remains low throughout. The study of optical orthogonal codes has been motivated by an application in a code-division multiple-access fiber optic channel. The use of optical orthogonal codes enables a large number of asynchronous users to transmit information efficiently and reliably. The thumbtack-shaped autocorrelation facilitates the detection of the desired signal, and low-profiled crosscorrelation reduces interference from unwanted signals. In addition to the wide-hand multiple-access system, optical orthogonal codes also find applications in mobile radio, spread-spectrum communications, and radar and sonar signal design. Methodologies in the design and analysis of optical orthogonal codes with tools from projective geometry, the greedy algorithm, iterative constructions, algebraic coding theory, block design, and various other combinatorial disciplines are discussed.
Augmented Exhibitions Using Natural Features

In this paper, we propose an augmented reality application for museum exhibitions using natural features instead of calibrated fiducials to recognize paintings and recover their pose. The proposed system utilizes an adapted Multiple View Kernel Projection (MVKP), which combines a multiple view training stage for geometric invariance and kernel projection based on Walsh-Hadamard kernels for feature description. We demonstrate that its real-time performance and robustness to lighting and viewpoint changes make it ideal for AR applications like AR exhibition systems. After obtaining the painting’s index, the system retrieves related information from a remote server and displays it as virtual content overlaid on top of the painting image. Experimental results on a real-world painting exhibition have demonstrated the effectiveness of the proposed approach.
Investigation of alternative strategies and quality measures for controlling the growth process of the growing hierarchical self-organizing map

The self-organizing map (SOM) is a very popular neural network model for data analysis and visualization of high-dimensional input data. The growing hierarchical self-organizing map (GHSOM) - being one of the many architectures based on the SOM - has the property of dynamically adapting its architecture during training by map growth as well as creating a hierarchical structure of maps, thus reflecting hierarchical relations in the data. This allows for viewing portions of the data at different levels of granularity. We review different SOM quality measures and also investigate alternative strategies as candidates for guiding the growth process of the GHSOM in order to improve the hierarchical representation of the data.
Binary Differential Evolution algorithm with new mutation operator

Differential Evolution (DE) algorithm is well known real parameter optimization method and has been successfully applied in many different fields. The operators used in DE are simple, however, the mechanism in which the operators are defined, makes it impossible to apply the standard DE to combinatorial problems directly. A novel binary DE was proposed to extend DE to solve binary space optimization problems. New mutation rules based on knowledge was used to guide the mutation operator. Initial experiment results indicate the effectiveness of the new mutation operator and feasibility of DE operating in binary space.
Sharing Underwriters with Rivals: Implications for Competition in Investment Banking

We conjecture that issuing firms seek to avoid sharing underwriters with their product-market rivals in order to limit the risk that strategically sensitive information is leaked to a rival firm via the underwriter relationship. We investigate this conjecture in a sample of 5,272 equity deals and 12,453 debt deals by large U.S. firms between 1975 and 2003. Using several distinct sources ofidentification, we find that this phenomenon is at least as important in determining the choice of lead underwriter as the bank s reputation or the issuing firm s existing relationship with the underwriter. We argue that this finding has important implications for understanding the nature of competition among investment banks, the durability of underwriting relationships, the successof entrants, and the likely impact of investment bank mergers on market power.
Analysis of Emotion EEG Classification Based on GA-Fisher Classifier

Emotion classification is a research hotspot in fields such as psychology and physiology. The categorical scales used recently need to be further researched for their subjective factors and accuracy influence. This paper presents an effective method which integrates GA-Fisher classifier and EEG, and we have got good classification effects by doing experiments on four emotions: excitement, fear, oscitancy, awaking. The results show that: (1) The classification accuracy rate between excitement and fear is 88.45%; and among excitement, fear and oscitancy for 86.71%; excitement, fear, oscitancy, and awaking for 84.70%; (2) the classifier introduced here is obviously better than the classical PCA-Fisher classifier (whose accuracy rate is 79.82% - 82.74%).
Ear biometrics in computer vision

A class of biometrics based upon ear features is introduced for use in the development of passive identification systems. The viability of the proposed biometric is shown both theoretically in terms of the uniqueness and measurability over time of the ear, and in practice through the implementation of a computer vision based system. Each subject's ear is modeled as an adjacency graph built from the Voronoi diagram of its curve segments. We introduce a novel graph matching based algorithm for authentication which takes into account the erroneous curve segments which can occur due to changes (e.g., lighting, shadowing, and occlusion) in the ear image. This class of biometrics is ideal for passive identification because the features are robust and can be reliably extracted from a distance.
On the Mining of Cointegrated Econometric Models

Research and development in data mining started with the extraction of association rules from vast amount of data. Today, data mining has evolved in a wide variety of directions, ranging from complexity control of algorithms to the development of applications for many domains, such as counter terrorism, medical diagnosing, marketing and so on (Antonie, Zaïane & Coman, 2001; Bach, 2003; Banek, Min Tjoa & Stolba, 2006; Bhattacharyya, 1999; Choenni, 2000; Wang & Han, 2000). The extraction of econometric models, however, has received relatively little attention in the field of data mining. An econometric model is a model that specifies the statistical relationship that is believed to hold between its variables. These models play a central role in many fields of research and become increasingly important in forecasting tools. For example, in finance, stock prices may be expressed in terms of other stock prices and macro-economic variables, such as industrial production and interest rates (Cheung & Ng, 1998; Nasseh & Strauss, 2000; Pesaran & Timmermann, 2000). Another example, within government forecasting, is the modelling of recorded crime, which may be expressed in terms of demographic and AbstrAct