Miracle-dz/UniFAR-FTUs huggingface dataset:
A High Capacity Information Hiding Algorithm in Color Image

One of the important objectives of information hiding research is that secret information is embed as much as possible without the perception of the carrier is affected. A hiding information algorithm of adaptive multiple plane-bit based on space domain in color image is proposed, which has low computing complexity and high capacity of information hiding. The main idea of this algorithm is to judge each pixel at first, then embed hidden information in the designated point behind the highest non-zero bit until another designated point according to the human visual characteristics. The experimental results show hidden information capacity of this algorithm is much larger than LSB algorithm, and security is much higher than LSB algorithm on the premise of that the visual effect of image is not affected.
Robust vision-based localization by combining an image-retrieval system with Monte Carlo localization

In this paper, we present a vision-based approach to mobile robot localization that integrates an image-retrieval system with Monte Carlo localization. The image-retrieval process is based on features that are invariant with respect to image translations and limited scale. Since it furthermore uses local features, the system is robust against distortion and occlusions, which is especially important in populated environments. To integrate this approach with the sample-based Monte Carlo localization technique, we extract for each image in the database a set of possible viewpoints using a two-dimensional map of the environment. Our technique has been implemented and tested extensively. We present practical experiments illustrating that our approach is able to globally localize a mobile robot, to reliably keep track of the robot's position, and to recover from localization failures. We furthermore present experiments designed to analyze the reliability and robustness of our approach with respect to larger errors in the odometry.
PTEN Deletion in Prostate Cancer Cells Does Not Associate with Loss of RAD51 Function: Implications for Radiotherapy and Chemotherapy

Purpose: PTEN deletions in prostate cancer are associated with tumor aggression and poor outcome. Recent studies have implicated PTEN as a determinant of homologous recombination (HR) through defective RAD51 function. Similar to BRCA1/2-defective tumor cells, PTEN-null prostate and other cancer cells have been reported to be sensitive to PARP inhibitors (PARPi). To date, no direct comparison between PTEN and RAD51 expression in primary prostate tumors has been reported. Experimental Design: Prostate cancer cell lines and xenografts with known PTEN status (22RV1-PTEN+/+, DU145-PTEN+/−, PC3-PTEN−/−) and H1299 and HCT116 cancer cells were used to evaluate how PTEN loss affects RAD51 expression and PARPi sensitivity. Primary prostate cancers with known PTEN status were analyzed for RAD51 expression. Results: PTEN status is not associated with reduced RAD51 mRNA or protein expression in primary prostate cancers. Decreased PTEN expression did not reduce RAD51 expression or clonogenic survival following PARPi among prostate cancer cells that vary in TP53 and PTEN. PARPi sensitivity instead associated with a defect in MRE11 expression. PTEN-deficient cells had only mild PARPi sensitivity and no loss of HR or RAD51 recruitment. Clonogenic cell survival following a series of DNA damaging agents was variable: PTEN-deficient cells were sensitive to ionizing radiation, mitomycin-C, UV, H2O2, and methyl methanesulfonate but not to cisplatin, camptothecin, or paclitaxel. Conclusions: These data suggest that the relationship between PTEN status and survival following DNA damage is indirect and complex. It is unlikely that PTEN status will be a direct biomarker for HR status or PARPi response in prostate cancer clinical trials. Clin Cancer Res; 18(4); 1015–27. ©2011 AACR.
Approximating the distribution of fitness over hamming regions

The distribution of fitness values across a set of states sharply influences the dynamics of evolutionary processes and heuristic search in combinatorial optimization. In this paper we present a method for approximating the distribution of fitness values over Hamming regions by solving a linear programming problem that incorporates low order moments of the target function. These moments can be retrieved in polynomial time for select problems such as MAX-k-SAT using Walsh analysis. The method is applicable to any real function on binary strings that is epistatically bounded and discrete with asymptotic bounds on the cardinality of its codomain. We perform several studies on the ONE-MAX and MAX-k-SAT domains to assess the accuracy of the approximation and its dependence on various factors. We show that the approximation can accurately predict the number of states within a Hamming region that have an improving fitness value.
Directional Distributional Similarity for Lexical Expansion

Distributional word similarity is most commonly perceived as a symmetric relation. Yet, one of its major applications is lexical expansion, which is generally asymmetric. This paper investigates the nature of directional (asymmetric) similarity measures, which aim to quantify distributional feature inclusion. We identify desired properties of such measures, specify a particular one based on averaged precision, and demonstrate the empirical benefit of directional measures for expansion.
Multilingual Semantic Role Labelling with Markov Logic

This paper presents our system for the CoNLL 2009 Shared Task on Syntactic and Semantic Dependencies in Multiple Languages (Hajic et al., 2009). In this work we focus only on the Semantic Role Labelling (SRL) task. We use Markov Logic to define a joint SRL model and achieve the third best average performance in the closed Track for SRLOnly systems and the sixth including for both SRLOnly and Joint systems.
Sensitivity of multi-source SAR backscatter to changes of forest aboveground biomass

Accurate estimates of aboveground biomass (AGB) from forest after disturbance could reduce the uncertainties in carbon budget of terrestrial ecosystem and provide critical information to related carbon policy. Yet the loss of carbon from forest disturbance and the gain from post-disturbance recovery have not been well assessed. In this study, sensitivity analysis was conducted to investigate: (1) influence of factors other than the change of AGB (i.e. distortion caused by incident angle, soil moisture) on SAR backscatter; (2) feasibility of cross-image calibration between multi-temporal and multi-sensor SAR data; and (3) possibility of applying normalized backscatter to detect the post-disturbance AGB recovery. A semi-automatic empirical model was proposed to reduce the incident angle effect. Then, a cross-image normalization procedure was performed in order to remove the radiometric distortions among multi-source SAR data. The results indicate that effect of incident angle and soil moisture on SAR backscatter could be reduced by the proposed procedure, and a detection of biomass changes is possible using multi-temporal and multi-sensor SAR data.
APPROXIMATE METHODS IN SEMANTICS FOR THE INTERNET: AN INTRODUCTORY MAP TO QUANTITATIVE SEMANTICS

This preface offers a conceptual framework for putting in context the extensive work that has been done in areas related to semantic similarity measuring, approximate semantic methods, document clustering and grouping, and many others that we call generically “Quantitative Semantics”. We present some of the most relevant works in these areas, classifying them so that a kind of map emerges, allowing a reader to understand the bigger picture of this tremendously relevant area in many text-processing tasks. As part of this framework, we provide a brief explanation for the works herein exposed, giving to the reader a scaffolding structure where the works in this book can be conceptually attached.
Exploring Evolving Role(s) of Literacy in Secondary Preservice Teachers’ Work: A Comparative Case Study

ABSTRACT While literacy courses are common in preservice teacher education programs, many secondary teacher candidates struggle to the see the relevance of literacy to their professional work. By exploring literacy in relation to personal, professional, and disciplinary identities, teacher candidates may better be able to embrace literacy integration as an important part of their larger professional work. This study examines how two teachers, Emma (art) and Lisa (physical education/dance), evolve in their understanding and implementation of literacy during a one-semester secondary literacy course. Given opportunities to engage with literacy through reflection on their personal experiences and within discipline-rich professional contexts through lesson planning, these two teachers demonstrate subtle but important shifts in both literacy use and perspective toward the role of literacy in their future professional practice.
Media Coverage of AIDS, Cancer, and Sexually Transmitted Diseases: A Test of the Public Arenas Model

This study explores the development and maintenance of topics on the public agenda and tests whether, for a new issue to compete for attention, an old issue must be displaced. This study finds little support for that assumption, and argues that the maintenance of topics is complex and the displacement effect is not as powerful as once assumed.
DESIGN, IMPLEMENTATION AND TESTING OF THE MAP RADIOMETERS

The Microwave Anisotropy Probe ( MAP) satellite, launched June 30, 2001, will produce full sky ma ps of the cosmic microwave background radiation in 5 frequency ba nds spanning 20 106 GHz. MAP contains 20 differential radiometers built with High Electron Mobilit y Transistor (HEMT) amplifiers with passively cooled input stages. The design and test techniques used to evaluat e nd minimize systematic errors and the pre-launch performance of the radiometers for all five bands are present d. Subject headings:cosmology: cosmic microwave background—instrumentation : detectors—space vehicles: instruments
Global-to-Local Shape Matching for Liver Segmentation in CT Imaging

We propose a two-stage algorithm to segment the liver in CT images. First, we estimate the pose and global shape properties using a statistical shape model defined in the low dimensional space spanned by a training set of shapes. Then, we apply a template matching procedure to recover local deformations that were not present in the learning set. In both steps, we optimize the same image term: the likelihood of the intensity inside the region of interest and its background. The method requires a single seed point inside the liver for the initialization. We show that this global-to-local strategy is able to recover livers with peculiar shapes in arbitrary poses.
A HYSTERESIS FOR A DS SUPERALLOY UNDER THERMOMECHANICAL FATIGUE

Cyclic plasticity and creep are the primary design considerations of 1 and 2 stage gas turbine blades. Directionally-solidified (DS) Ni-base materials have been developed to provide (1) greater creep ductility and (2) lower minimum creep rate in solidification direction compared to other directions. Tracking the evolution of deformation in DS structures necessitates a constitutive model having the functionality to capture rate-, temperature-, history-, and orientation-dependence. Historically, models rooted in microstructurally-based viscoplasticity simulate the response of long-crystal, dual-phase Ni-base superalloys with extraordinary fidelity; however, a macroscopic approach having reduced order is leveraged to simulate LCF, creep, and creep-fatigue responses with equally high accuracy. This study applies uncoupled creep and plasticity models to predict the TMF of a generic DS Ni-base, and an anisotropic yield theory accounts for transversely-isotropic strength. Due to the fully analytic determination of material constants from mechanical test data, the model can be readily tuned for materials in either peakor base-loaded units. Application of the model via a parametric study reveals trends in the stabilized hysteresis response of under isothermal fatigue, creep-fatigue, thermomechanical fatigue, and conditions representative of inservice components. Though frequently considered in design and maintenance of turbine materials, non-isothermal fatigue has yet to be accurately predicted for a generalized set of loading conditions. The formulations presented in this study address this knowledge gap using extensions of traditional power law constitutive models.
Analysing Dependency Dynamics in Web Data

Modern web sites provide easy access to large amounts of data via open application programming interfaces. Users interacting with these sites constantly change the underlying data sets, which can be represented in graph-structured form. Nodes in these dynamic graph structures exhibit dependencies over time (for example, one node changes before other nodes change in the same way). Analysing these dependencies is crucial for understanding and predicting the dynamics inherent to temporally changing graph structures on the web. When the graphs become large however, it is not feasible to take into account all properties of the graph and in general it is unclear how to choose the appropriate features. Moreover, comparing two nodes becomes difficult, if the nodes do not share exactly the same features. In this work we propose an algorithm that automatically learns the features that govern temporal dependencies between nodes in large dynamic graph structures. We present preliminary results of applying the algorithm to data collected from the web, discuss potential extensions of the framework and anticipate how a major problem in machine learning, sparse data, could be tackled by leveraging Linked Data.
Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial Optimization

The max-product {belief propagation} (BP) is a popular message-passing heuristic for approximating a maximum-a-posteriori (MAP) assignment in a joint distribution represented by a graphical model (GM). In the past years, it has been shown that BP can solve a few classes of linear programming (LP) formulations to combinatorial optimization problems including maximum weight matching, shortest path and network flow, i.e., BP can be used as a message-passing solver for certain combinatorial optimizations. However, those LPs and corresponding BP analysis are very sensitive to underlying problem setups, and it has been not clear what extent these results can be generalized to. In this paper, we obtain a generic criteria that BP converges to the optimal solution of given LP, and show that it is satisfied in LP formulations associated to many classical combinatorial optimization problems including maximum weight perfect matching, shortest path, traveling salesman, cycle packing, vertex/edge cover and network flow.
The influence of the sound environment on the welfare of zoo-housed callitrichine monkeys

x Chapter One: Introduction: Sound and its significance . 1 Chapter Two: Fecal glucocorticoid metabolite responses to management stressors and social change in four species of callitrichine monkeys . 32 Chapter Three: The influence of waterfall sounds and access to off-exhibit areas on the behavior and exhibit use of three species of callitrichine monkeys . 58 Chapter Four: Do zoo animals use off-exhibit areas to avoid noise? A case study exploring the influence of sound on the behavior, physiology, and exhibit use of two pied tamarins (Saguinus bicolor) . 81 Chapter Five: The response of callitrichine monkeys to auditory stimuli and the importance of exhibit choices . 98 Chapter Six: A pilot investigation on the use of startle reactivity as a measure of affect in callitrichine monkeys . 114 Chapter Seven: General discussion and future outlook . 134 References . 143
Probabilistic Analysis Using Theorem Proving

Traditionally, computer simulation techniques are used to perform probabilistic analysis. However, they provide less accurate results and cannot handle large-scale problems due to their enormous CPU time requirements. Recently, a significant amount of formalization has been done in higher-order logic that allows us to conduct precise probabilistic analysis using theorem proving and thus overcome the limitations of the simulation based probabilistic analysis approach. Some major contributions include the formalization of both discrete and continuous random variables and the verification of corresponding probabilistic and statistical properties. This book presents a concise description of the infrastructures behind these capabilities and their utilization to conduct the probabilistic analysis of real-world systems. The case studies of the round-off error of a digital processor, the Coupon Collector's problem and the Stop-and-Wait protocol are used to illustrate the proposed analysis approach. Designed as an independent research tool, the book presents a well-thought-out treatment of a rapidly emerging multidisciplinary field across Mathematics, Computer Science and Engineering.
Reading Comprehension Instruction for Adolescents with Learning Disabilities: A Reality Check

Reading comprehension is a significant concern for adolescents with learning disabilities (LD), particularly in secondary schools in the United States (US) where content is taught primarily through textbooks. Surprisingly little is known about the actual reading instruction for students with LD in secondary classrooms. Thus, the purpose of this study was to examine the reading comprehension instruction in US secondary special education classrooms. Eight special education teachers in urban high schools were observed and interviewed. Findings showed that teachers implemented a number of reading comprehension practices, not all were considered “best practice”. The most frequently observed practices included reading aloud, questioning, seatwork, activating prior knowledge, and using graphic organizers. Explicit instruction in how and when to use reading comprehension strategies, however, was not observed. This study reveals the extent to which evidence-based reading comprehension practices are not making their way into secondary reading classrooms and offers insight into factors that teachers state as influencing their instruction for students with LD.
2013 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops Exploring Audio Storytelling in Mobile Exergames to Affect the Perception of Physical Exercise

Exergames (video games that combine exercise and play) can make the experience of physical activities more enjoy­ able. Mobile exergames are particularly interesting as they can be used for outdoors, open-air physical activities. Unfortunately, current mobile exergames tend to require the player to frequently or continuously look at the screen. This can be hard to do while exercising, and it also requires the player to considerably distract visual attention from the surrounding physical environment, introducing safety issues in activities such as outdoor running. In this paper, we focus on two main goals. First, we explore how to use audio storytelling techniques to make physical exercise more engaging and enjoyable by exploiting a soundscape that provides prompt feedback in response to players' activity and does not require the player to look at the screen during running. Second, we study if the exergame is fun for users and if it positively affects the perception of the running experience. We measure important variables such as level of physical activity in player's lifestyle and player's physical activity enjoyment through validated methods employed in the medical literature. The results of the study show that the use of audio storytelling techniques in mobile exergames is appreciated by users, and the exergame has positive effects on the perception of physical exercise.
Theory and Practice of Logic Programming

We present a novel general resource analysis for logic programs based on sized types. Sized types are representations that incorporate structural (shape) information and allow expressing both lower and upper bounds on the size of a set of terms and their subterms at any position and depth. They also allow relating the sizes of terms and subterms occurring at different argument positions in logic predicates. Using these sized types, the resource analysis can infer both lower and upper bounds on the resources used by all the procedures in a program as functions on input term (and subterm) sizes, overcoming limitations of existing resource analyses and enhancing their precision. Our new resource analysis has been developed within the abstract interpretation framework, as an extension of the sized types abstract domain, and has been integrated into the Ciao preprocessor, CiaoPP. The abstract domain operations are integrated with the setting up and solving of recurrence equations for inferring both size and resource usage functions. We show that the analysis is an improvement over the previous resource analysis present in CiaoPP and compares well in power to state of the art systems.
Genetic Analysis of Hedgehog Signaling in Ventral Body Wall Development and the Onset of Omphalocele Formation

Background An omphalocele is one of the major ventral body wall malformations and is characterized by abnormally herniated viscera from the body trunk. It has been frequently found to be associated with other structural malformations, such as genitourinary malformations and digit abnormalities. In spite of its clinical importance, the etiology of omphalocele formation is still controversial. Hedgehog (Hh) signaling is one of the essential growth factor signaling pathways involved in the formation of the limbs and urogenital system. However, the relationship between Hh signaling and ventral body wall formation remains unclear. Methodology/Principal Findings To gain insight into the roles of Hh signaling in ventral body wall formation and its malformation, we analyzed phenotypes of mouse mutants of Sonic hedgehog (Shh), GLI-Kruppel family member 3 (Gli3) and Aristaless-like homeobox 4 (Alx4). Introduction of additional Alx4Lst mutations into the Gli3Xt/Xt background resulted in various degrees of severe omphalocele and pubic diastasis. In addition, loss of a single Shh allele restored the omphalocele and pubic symphysis of Gli3Xt/+; Alx4Lst/Lst embryos. We also observed ectopic Hh activity in the ventral body wall region of Gli3Xt/Xt embryos. Moreover, tamoxifen-inducible gain-of-function experiments to induce ectopic Hh signaling revealed Hh signal dose-dependent formation of omphaloceles. Conclusions/Significance We suggest that one of the possible causes of omphalocele and pubic diastasis is ectopically-induced Hh signaling. To our knowledge, this would be the first demonstration of the involvement of Hh signaling in ventral body wall malformation and the genetic rescue of omphalocele phenotypes.
Coherent Quantum H∞ Control via a Strict Bounded Real Quantum Controller*

Abstract We present a systematic method to synthesize a coherent quantum robust H ∞ controller for a class of linear complex quantum stochastic systems, which is defined only in terms of annihilation operators, with norm-bounded structured uncertainties. This controller is required to be stable and strict bounded real in order to be physically realizable. The main idea of our approach is to introduce an additional uncertainty to form an artificial uncertain quantum system used to design the desired quantum controller. The H ∞ control objective is to achieve a strict bounded real closed loop quantum system with a specified disturbance attenuation level. The solution to this control problem is given in terms of stabilizing solutions to the parameterized complex Riccati equations.