Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduction Techniques for Training Support Vector Machines

Recently two kinds of reduction techniques which aimed at saving training time for SVM problems with nonlinear kernels were proposed. Instead of solving the standard SVM formulation, these methods explicitly alter the SVM formulation, and solutions for them are used to classify data. The first approach, reduced support vector machine (RSVM) [21], preselects a subset of data as support vectors and solves a smaller optimization problem. The second approach [11] uses imcomplete Cholesky factorization (ICF) to obtain a low-rank approximation of the kernel matrix. Therefore, an easier optimization problem is obtained. We find that several issues of their practical uses have not been fully discussed yet. For example, we do not know if they possess comparable generalization ability as the standard SVM. In addition, we would like to see for how large problems they outperform SVM on training time. In this thesis we show that the formulation of each technique is already in a form of linear SVM and discuss several suitable implementations. Experiments indicate that in general the test accuracy of both techniques is a little lower than that of the standard SVM. In addition, for problems with up to tens of thousands of data, if the percentage of support vectors is not high, existing implementations for SVM is quite competitive on the training time. Thus, the two techniques will be mainly useful for either larger problems or those with many support vectors. Experiments in this thesis also serve as comparisons of (1) different implementations for linear SVM; (2) standard SVM using linear and quadratic cost functions; and (3) two ICF algorithms for positive definite dense matrices.
Semantic distance and terminology structuring methods for the detection of semantically close terms

The identification of semantically similar linguistic expressions despite their formal difference is an important task within NLP applications (information retrieval and extraction, terminology structuring.) We propose to detect the semantic relatedness between biomedical terms from the pharmacovigilance area. Two approaches are exploited: semantic distance within structured resources and terminology structuring methods applied to a raw list of terms. We compare these methods and study their complementarity. The results are evaluated against the reference pharmacovigilance data and manually by an expert.
Estrogen Exposure, Metabolism, and Enzyme Variants in a Model for Breast Cancer Risk Prediction

Estrogen is a well-known risk factor for breast cancer. Current models of breast cancer risk prediction are based on cumulative estrogen exposure but do not directly reflect mammary estrogen metabolism or address genetic variability between women in exposure to carcinogenic estrogen metabolites. We are proposing a mathematical model that forecasts breast cancer risk for a woman based on three factors: (1) estimated estrogen exposure, (2) kinetic analysis of the oxidative estrogen metabolism pathway in the breast, and (3) enzyme genotypes responsible for inherited differences in the production of carcinogenic metabolites. The model incorporates the main components of mammary estrogen metabolism, i.e. the conversion of 17β-estradiol (E2) by the phase I and II enzymes cytochrome P450 (CYP) 1A1 and 1B1, catechol-O-methyltransferase (COMT), and glutathione S-transferase P1 (GSTP1) into reactive metabolites, including catechol estrogens and estrogen quinones, such as E2-3,4-Q which can damage DNA. Each of the four genes is genotyped and the SNP data used to derive the haplotype configuration for each subject. The model then utilizes the kinetic and genotypic data to calculate the amount of E2-3,4-Q carcinogen as ultimate risk factor for each woman. The proposed model extends existing models by combining the traditional “phenotypic” measures of estrogen exposure with genotypic data associated with the metabolic fate of E2 as determined by critical phase I and II enzymes. Instead of providing a general risk estimate our model would predict the risk for each individual woman based on her age, reproductive experiences as well as her genotypic profile.
Region-Adaptive Watermarking System and Its Application

Digital image watermarking is one of the most widely used techniques for protection of ownership rights of digital images. The main objective of the majority of research in this area remains to be the improvement in imperceptibility and robustness to attack. In this paper, we present a novel watermarking algorithm using a region-adaptive approach to further improve upon these criteria. The watermark data is embedded on different regions of the host image using a combination of discrete wavelet transform and singular value decomposition technique. In addition, there is a novel use the region-adaptive watermarking technique as a means to detect if certain types of attack have occurred. This is a unique feature of our watermarking algorithm which separates it from other state-of-the-art watermarking techniques. The watermark detection process uses coefficients derived from the region-adaptive watermarking algorithm in a linear classifier. The experiment conducted to validate this feature shows that all watermark attacks can be correctly detected and identified.
Multiscale Modeling of Nanocomposite Structures with Defects

A method for the numerical modeling of mechanical behavior of nanocomposite materials reinforced with the carbon nanotubes, based on the computational homogenization as a multiscale method, is presented. The matrix reinforcement interactions, based on the weak van der Waals forces are incorporated into the multiscale model and are represented by the nonlinear rod elements. The reinforcements, i.e. carbon nanotubes, are modeled as a space frame structure, using beam finite elements. Computational homogenization and representative volume element (RVE) are the basis of the presented numerical model of the nanocomposites. Nanoscale model is based on beam and non-linear rod finite elements. An algorithm is developed for the analysis of the presented nanostructure, and for the purpose of the software verification, examples, i.e. models of the nanocomposite material are presented. Also, the nanocomposite model with various vacancy defects in the reinforcement, i.e. nanotube, has been prepared and the obtained results are compared and discussed.Keywords Nanocomposite materials · Carbon nanotubes · Multiscale modelling · Computational homogenization
Use of natural rubber prophylactics waste as a potential filler in styrene-butadiene rubber compounds

Owing to the unstable nature of the latex compound and the strict specifications in the quality of latex products such as condoms and examination gloves, the rejection in the latex industry comes to about 10 to 15% of the rubber consumed. These latex rejects contain about 95% rubber hydrocarbon of very high quality. A cost-effective technique has been developed for the reuse of natural rubber (NR) prophylacties waste in styrene–butadiene rubber (SBR). The influence of powdered latex rejects on the curing characteristics, mechanical properties, and failure behavior of SBR has been investigated. More emphasis is placed on the effect of both particle size and the loading of latex waste filler. Swelling studies were carried out to establish the degree of crosslinking of SBR and to assess the extent of interaction between the matrix and latex waste filler of varying particle sizes. A three layer model has been set up to study the diffusion of sulfur from the matrix phase to the filler phase. Scanning electron microscopy has been used to analyze the particle morphology, filler dispersion, and filler-matrix interface adhesion. The results of the study revealed that NR prophylactics rejects can be used effectively as a potential filler in SBR up to about 40 phr loading. © 1996 John Wiley & Sons, Inc.
TEPAWSN - A tool environment for Wireless Sensor Networks

We strongly believe that Wireless Sensor Network (WSN) development must be supported from the design phase by formal methods to achieve strong results on correctness, performance, cost and efficiency. In this paper, we propose a tool environment called TEPAWSN for WSNs which will make a relevant contribution to the WSN research by facilitating the design and analysis of power aware WSNs.
Material development aspects of an oxidation protection system for a reinforced carbon-carbon composite. [for Space Shuttle leading edges]

The paper describes the procedures which led to selection of a diffusion-coated siliconized oxidation-resistant reinforced carbon-carbon composite as a candidate for use in the leading edge structure of the Space Shuttle for the purpose of providing thermal protection. Materials were evaluated on the basis of oxidation-inhibitor performance, strength properties, and fabricability. Compounds of titanium, tantalum, zirconium, silicon, hafnium, aluminum, and boron were compounded with the reinforced carbon-carbon material in two different processing techniques to discover an oxidation-inhibited system which provided multicycle protection at temperatures up to 4000 F. Details of the manufacture and testing of the reinforced carbon-carbon composites are provided.
3D TEM Tomography of Templated Bilayer Films of Block Copolymers

Transmission electron microscope (TEM) tomography was used to visualize the morphology and 3D connectivity of a lithographically templated, self‐assembled bilayer film of cylinder‐forming 45.5 kg/mol polystyrene‐block‐polydimethylsiloxane. The structure, formed after a 5 min solvothermal anneal, was imaged with a resolution of ≈3 nm in 3D, enabling a comparison between measurement and self‐consistent mean‐field theory (SCFT) calculations. Images of etched and unetched samples showed that etching collapsed the PDMS microdomain structure and reduced the template dimensions. In addition to the general comparison between modeled and measured dimensions, the tomography revealed connections between the orthogonal layers of cylinders at their crossing points. Comparison with the SCFT model, even under solvothermal annealing conditions, shows that it is helpful in understanding the detailed nanoscale structure of features created by directed self‐assembly (DSA), which is essential in developing nanomanufacturing processes based on DSA.
Binary Vulnerability Exploitability Analysis

In this paper, we propose reversed taint analysis to dig out the root cause of the vulnerability leading to crash. In order to increase the efficiency, we propose that during the analysis process, we should only taint the EIP register when the crash happens and then trace back to analyze the data and operations, until we find out the influential inputs that can be controlled by the users. In addition, we suggest that only the exploits could confirm exploitable vulnerabilities. To confirm the exploitability, we propose degraded symbolic execution to generate exploits efficiently by only symbolizing the user's input found in the reversed taint analysis to decrease the number of symbolic variables, in other words, decrease the number of path we need to execute. We also discuss how the exploit mitigations of modern operating system affect the judgment on exploitability of vulnerabilities. And we found that the exploitability of a vulnerability should be judged according to the version of operating system and mitigations.
Conjugative Transfer of the Integrative Conjugative Elements ICESt1 and ICESt3 from Streptococcus thermophilus

ABSTRACT Integrative and conjugative elements (ICEs), also called conjugative transposons, are genomic islands that excise, self-transfer by conjugation, and integrate in the genome of the recipient bacterium. The current investigation shows the intraspecies conjugative transfer of the first described ICEs in Streptococcus thermophilus, ICESt1 and ICESt3. Mitomycin C, a DNA-damaging agent, derepresses ICESt3 conjugative transfer almost 25-fold. The ICESt3 host range was determined using various members of the Firmicutes as recipients. Whereas numerous ICESt3 transconjugants of Streptococcus pyogenes and Enterococcus faecalis were recovered, only one transconjugant of Lactococcus lactis was obtained. The newly incoming ICEs, except the one from L. lactis, are site-specifically integrated into the 3′ end of the fda gene and are still able to excise in these transconjugants. Furthermore, ICESt3 was retransferred from E. faecalis to S. thermophilus. Recombinant plasmids carrying different parts of the ICESt1 recombination module were used to show that the integrase gene is required for the site-specific integration and excision of the ICEs, whereas the excisionase gene is required for the site-specific excision only.
Bayesian analysis and free market trade within the Roman Empire

Abstract The trade networks of the Roman Empire are among the most intensively researched large-scale market systems in antiquity, yet there is no consensus on the economic structure behind this vast network. The difficulty arises from data fragmentation and the lack of formal analytical methods. Here, the authors present a Bayesian analysis quantifying the extent to which four previously proposed hypotheses match the evidence for the market system in Roman olive oil. Results suggest that the size of economic agents involved in this network followed a power-law distribution, strongly indicating the presence of free market structures supplying olive oil to Rome. This new analysis offers an important tool to researchers exploring the impact of trade on the dynamics of past societies.
Design and Experiments of a Novel Quadruped Robot with Wheel-Leg Structure

Wheeled mobile robots are widely used in various scenarios, but their mobility performance is constrained by various factors such as terrain. A new type of quadruped robot with a wheel leg structure is proposed to address this issue, following the design criteria of high stiffness, lightweight, high stability, low control complexity, and low cost. Firstly, the overall mechanical structure design was analyzed, and a detailed introduction was given to the unique leg load-bearing structure; Secondly, the workspace of the robot was analyzed, and the control strategy and hardware system of the robot were introduced in detail; Finally, the feasibility of the robot design was verified through experiments. The experimental results demonstrate that the robot exhibits excellent performance in smoothly traversing single-side slopes and possesses significant potential in overcoming structured obstacles.
Imaging cyclophosphamide-induced intramedullary apoptosis in rats using 99mTc-radiolabeled annexin V.

UNLABELLED Intramedullary apoptosis of hematopoietic tissue is believed to play a major role in the pathophysiology of myelodysplastic syndrome. Annexin V, a specific marker of the early to intermediate phases of apoptosis, has been applied to the in vitro study of bone marrow aspirates. A noninvasive measure of intramedullary apoptosis in vivo that could serially monitor the clinical progression of myelodysplastic syndrome may be helpful. METHODS We used 99mTc-radiolabeled annexin V and radionuclide gamma camera imaging to serially study the sites, extent, and severity of intramedullary apoptosis induced by cyclophosphamide treatment. RESULTS Intravenously administered radiolabeled annexin V localized preferentially in the femur, pelvis, vertebrae, and spleen; increased uptake in these organs was easily visualized as early as 8 h after injection of 100 mg/kg cyclophosphamide in 8- to 10-wk-old animals. Higher doses of cyclophosphamide (150 mg/kg) in animals of the same age increased annexin V uptake in the bone marrow and splenic tissue and delayed recovery of these organs as seen histologically compared with lower doses. Older animals, 5-6 mo old, showed a slower response to cyclophosphamide treatment and delayed recovery of bone marrow and splenic tissues. CONCLUSION Radiolabeled annexin V can be used to detect and directly quantify the degree of intramedullary and splenic apoptosis in a noninvasive fashion using current clinical radionuclide imaging equipment. Annexin V imaging may be useful clinically in the diagnosis and management of myelodysplastic syndrome.
Towards Automated Processing of Folk Song Recordings

Folk music is closely related to the musical culture of a specific nation or region. Even though folk songs have been passed down mainly by oral tradition, most musicologists study the relation between folk songs on the basis of symbolic music descriptions, which are obtained by transcribing recorded tunes into a score-like representation. Due to the complexity of audio recordings, once having the transcriptions, the original recorded tunes are often no longer used in the actual folk song research even though they still may contain valuable information. In this paper, we present various techniques for making audio recordings more easily accessible for music researchers. In particular, we show how one can use synchronization techniques to automatically segment and annotate the recorded songs. The processed audio recordings can then be made accessible along with a symbolic transcript by means of suitable visualization, searching, and navigation interfaces to assist folk song researchers to conduct large scale investigations comprising the audio material.
Dendritic Guanidines as Efficient Analogues of Cell Penetrating Peptides

The widespread application of cell penetrating agents to clinical therapeutics and imaging agents relies on the ability to prepare them on a large scale and to readily conjugate them to their cargos. Dendritic analogues of cell penetrating peptides, with multiple guanidine groups on their peripheries offer advantages as their high symmetry allows them to be efficiently synthesized, while orthogonal functionalities at their focal points allow them to be conjugated to cargo using simple synthetic methods. Their chemical structures and properties are also highly tunable as their flexibility and the number of guanidine groups can be tuned by altering the dendritic backbone or the linkages to the guanidine groups. This review describes the development of cell-penetrating dendrimers based on several different backbones, their structure-property relationships, and comparisons of their efficacies with those of known cell penetrating peptides. The toxicities of these dendritic guanidines are also reported as well as their application towards the intracellular delivery of biologically significant cargos including proteins and nanoparticles.
Mining partially annotated images

In this paper, we study the problem of mining partially annotated images. We first define what the problem of mining partially annotated images is, and argue that in many real-world applications annotated images are typically partially annotated and thus that the problem of mining partially annotated images exists in many situations. We then propose an effective solution to this problem based on a statistical model we have developed called the Semi-Supervised Correspondence Hierarchical Dirichlet Process (SSCHDP). The main idea of this model lies in exploiting the information pertaining to partially annotated images or even unannotated images to achieve semi-supervised learning under the HDP structure. We apply this model to completing the annotations appropriately for partially annotated images in the training data and then to predicting the annotations appropriately and completely for all the unannotated images either in the training data or in any unseen data beyond the training process. Experiments show that SSC-HDP is superior to the peer models from the recent literature when they are applied to solving the problem of mining partially annotated images.
Multitoe: high-precision interaction with back-projected floors based on high-resolution multi-touch input

Tabletop applications cannot display more than a few dozen on-screen objects. The reason is their limited size: tables cannot become larger than arm's length without giving up direct touch. We propose creating direct touch surfaces that are orders of magnitude larger. We approach this challenge by integrating high-resolution multitouch input into a back-projected floor. As the same time, we maintain the purpose and interaction concepts of tabletop computers, namely direct manipulation. We base our hardware design on frustrated total internal reflection. Its ability to sense per-pixel pressure allows the floor to locate and analyze users' soles. We demonstrate how this allows the floor to recognize foot postures and identify users. These two functions form the basis of our system. They allow the floor to ignore users unless they interact explicitly, identify and track users based on their shoes, enable high-precision interaction, invoke menus, track heads, and allow users to control high-degree of freedom interactions using their feet. While we base our designs on a series of simple user studies, the primary contribution on this paper is in the engineering domain.
Reasoning on a Highlighted User Model to Respond to Misconceptions

Responses to misconceptions given by human conversational partners very often contain information refuting possible reasoning which may have led to the misconceptions. Surprisingly there is a great deal of regularity in these responses across different domains of discourse. For instance, one reason a user might have given an object a property it does not have is that the user confused the object with another similar object. In correcting such a misconception, a human conversational partner is likely to point out this possible confusion.This work describes a method for generating responses like the one just described by reasoning on a highlighted model of the user to identify possible sources of the error. Through a transcript study a number of response strategies were abstracted. Each strategy was associated with a structural configuration of the user model. For example, the above mentioned strategy of pointing out a similar confused object is associated with a configuration of the user model that indicates the user believes there is an important similar object that has the property involved in the misconception. Upon finding that configuration in the highlighted user model, the system can respond with the associated strategy.Notice that the reasoning must be done on a highlighted user model since the perception of both an object's importance and its similarity with another object change with the perspective being taken on the domain. This paper investigates how domain perspective can be modeled to provide the needed highlighting and introduces a similarity metric that is sensitive to the highlighting provided by the domain perspective. Finally, the paper shows how the highlighting affects misconception responses.