Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Tags and Clustering to Identify Topic-Relevant Blogs

The Web has experienced an exponential growth in the use of weblogs or blogs. Blog entries are generally organised using tags, informally defined labels which are increasingly being proposed as a ‘grassroots’ answer to Semantic Web standards. Despite this, tags have been shown to be weak at partitioning blog data. In this paper, we demonstrate how tags provide useful, discriminating information where the blog corpus is initially partitioned using a conventional clustering technique. Using extensive empirical evaluation we demonstrate how tag cloud information within each cluster allows us to identify the most topic-relevant blogs in the cluster. We conclude that tags have a key auxiliary role in refining and confirming the information produced using typical knowledge discovery techniques.
Spectral indices of Galactic radio loops between 1420, 820 and 408 MHz

In this paper, the average brightness temperatures and surface brightnesses at 1420, 820 and 408 MHz of the six main Galactic radio-continuum loops are derived, as are their radio spectral indices. The temperatures and surface brightnesses of the radio loops are computed using data taken from radio-continuum surveys at 1420, 820 and 408 MHz. We have demonstrated the reality of Loops V and VI and present diagrams of their spectra for the first time. We derived the radio spectral indices of Galactic radio loops from radio surveys at three frequencies (1420, 820 and 408 MHz) and confirm them to be non-thermal sources. Diameters and distances of Loops I-VI were also calculated. The results obtained are in good agreement with current theories of supernova remnant (SNR) evolution and suggest that radio loops may have a SNR origin.
Evidence for a persistent and extensive greening trend in Eurasia inferred from satellite vegetation index data

[1] The northern latitudes have warmed by ∼0.8°C since the early 1970s, but not all areas have warmed equally. Eurasia shows an overall warming trend, while North America exhibits warming at a lower rate and even a slight cooling trend during the last 50 years in the eastern United States. We analyzed a recently developed satellite normalized difference vegetation index (NDVI) data set (July 1981 to December 1999) to assess vegetation response to these temperature changes. An index of persistence of the NDVI trend was used to generate patches of different levels of persistence. The persistence data were analyzed for patch area, patch perimeter, patch number, patch coherence, largest patch size, patch fragmentation, pixel contiguity, pixel clustering, and conditional probability of pixel adjacency. We address two questions: (1) Is there a difference in the spatial pattern of long-term NDVI increase in comparison to short-term increase? and (2) Are there differences in the spatial patterns of patches between Eurasia and North America? The results indicate a persistent and spatially extensive and connected greening trend in Eurasia, relative to North America. The regions showing short-term greening in Eurasia show a scattered pattern of spatially remote small patches. In North America the long-term greening pattern is spatially fragmented, and a mixture of short- and long-term NDVI increase is found, unlike in Eurasia. Therefore we conclude that the greening trend in Eurasia is more persistent and spatially extensive than in North America, which is qualitatively consistent with near-surface air temperature observations.
The method of detecting pulmonary nodules by snake model

The aim of detecting pulmonary nodules by computer-aided diagnostic system is reduce doctors' workload. Firstly, the part of pulmonary parenchyma should be extracted from a CT image. To extract the pulmonary parenchyma's contours well, we can utilize mathematical morphology filter. Then, Snake model is used to extract suspicious nodule's contours in pulmonary parenchyma. Finally, program will eliminate interference automatically based on the pathological features of pulmonary nodules and mark these suspicious nodules on CT image.
Virtual Nervous Systems for Self-Assembling Robots - A preliminary report

We define the nervous system of a robot as the processing unit responsible for controlling the robot body, together with the links between the processing unit and the sensorimotor hardware of the robot - i.e., the equivalent of the central nervous system in biological organisms. We present autonomous robots that can merge their nervous systems when they physically connect to each other, creating a "virtual nervous system" (VNS). We show that robots with a VNS have capabilities beyond those found in any existing robotic system or biological organism: they can merge into larger bodies with a single brain (i.e., processing unit), split into separate bodies with independent brains, and temporarily acquire sensing and actuating capabilities of specialized peer robots. VNS-based robots can also self-heal by removing or replacing malfunctioning body parts, including the brain.
On sliding mode control of a class of singularly perturbed systems under sensor noise

Since singularly perturbed system has many benefits such that the order of system can be reduced, there have been many researches about singularly perturbed system. On the other hand, sensor noise is frequently encountered phenomenon in many practical systems. Although there have been many researches considering sensor noise, as of now there have not been any researches which guarantee arbitrarily small ultimate bound of states of singularly perturbed system. In this note, we propose a novel sliding mode control with output feedback which guarantees arbitrarily small ultimate bound.
Argumentative Classiication of Extracted Sentences as a Rst Step towards Exible Abstracting

Knowledge about the rhetorical structure of a text is useful for automatic abstraction. We are interested in the automatic extraction of rhetorical units from the source text, units such as Problem Statement, Conclusions and Results. We want to use such extracts to generate high-compression abstracts of scientiic articles. In this paper, we present an extension of Kupiec, Pedersen and Chen's (1995) methodology for trainable statistical sentence extraction. Our extension additionally classiies the extracted sentences according to their rhetorical role.
Ultrasonic Elasticity Imaging as a Tool for Breast Cancer Diagnosis and Research

Ultrasonic elasticity imaging is a promising new tool for breast cancer diagnosis and management. Ultrasound is applied to sense small local tissue deformations noninvasively to image stiffness and thus exploit the large intrinsic stiffness contrast generated during the progression of many diseases in vivo . This paper briefly reviews several related approaches to breast elasticity imaging to explain some of the observed variability in breast imaging results. Preliminary clinical results from a population of 13 patients with small and nonpalpable breast lesions obtained with a low noise elasticity imaging algorithm developed in our group are then reported. All the benign lesions exhibited normal elasticity ranges. About half of the malignant lesions were undetected with elasticity imaging most likely because of their small size (<7mm) or softening from the addition of fatty-replaced tissue. Other malignant lesions were clearly identified as areas with extreme elasticity values compared to their surroundings. We observed that some malignant lesions did not exhibit any desmoplasic stiffening while others showed an uncommon softening. It is clear that by broadening the study population to include small and nonpalpable lesions, we see much variability in elasticity image findings.
Robust Parametric Image Registration using Genetic Algorithms and Newton Levenberg Marquardt

We present a hybrid method to perform parametric image registration. The objective is to find the best set of parameters of an affine transformation, which applied to the original image yields the closest match to a target image (possibly with noise). Hybridization occurs when Genetic Algorithms are able to determine rough areas of the parameter optimization space, but fail to produce fine tunings for those parameters. In that case, the Newton–Levenberg–Marquardt method is used to refine results. Another important combination of techniques results when we want to compare images. In this case, the fitness function needs to be robust enough to discard misleading information contained in outliers. Statistical techniques are employed in this case to be able to compare images in the presence of noise. The resulting implementation, called GA–SSD– ARC+ was compared against robust registration methods used in the area of image processing. GA–SSD–ARC+ outperforms the RANSAC and the Lorentzian Estimator methods when images are noisy or corrupted by outliers.
The Milgram-Holocaust Linkage: Challenging the Present Consensus

: Stanley Milgram’s assertion that his “Obedience to Authority” (OTA) experiments replicated, in a laboratory setting, quintessential features of perpetrator behaviour during the Holocaust has been widely challenged. Most contemporary scholarship on this issue, known as the “Milgram-Holocaust (M-H) linkage”, argues that Milgram’s experiments failed to capture important factors such as ideology, policy, bureaucracy and technology, which more fully explain perpetrator behaviour. However, it is argued here that when the obedience research programme is viewed from a different angle – that of being an emerging policy-driven bureaucratic process in pursuit of “scientific” goals with an impersonal means of inflicting harm – the interplay of factors such as ideology, policy, bureaucracy and technology did in fact play a central role in generating Milgram’s high baseline completion rate. Hence, there is a much stronger theoretical connection between the OTA experiments and the Nazi state’s perpetration of the Holocaust than the current scholarly consensus allows.
Control of machines with friction

1. Introduction. - 2. Friction in Machines. - 2.1. The Contemporary Model of Machine Friction. - 2.2. Boundary Lubricants: a Domain of Many Choices. - 2.3. Relaxation Oscillations. - 2.4. Friction Modeling in the Controls Literature. - 2.5. An Integrated Friction Model. - 3. Experiment Design. - 4. Repeatability. - 5. Break-Away Experiments. - 5.1. Experimental Issues in Measuring Break-Away Torque. - 5.2. Building the Compensation Table. - 6. Friction as a Function of Velocity. - 6.1. Analysis of Variance in the Motion Friction Data. - 6.2. Friction at Low Velocities. - 6.3. Friction During Compliant Motion. - 6.4. The Dahl Effect. - 6.5. The Stribeck Effect. - 6.6. Temporal Effects in the Rise and Decay of Friction. - 6.7. Variance in Friction as Process Noise. - 7. Analysis of Stick-Slip. - 7.1. Dimensional Analysis. - 7.2. Perturbation Analysis. - 7.3. The Impact of Static Friction Rising as a Function of Dwell Time. - 7.4. Integral Control. - 8. Demonstrations of Friction Compensation. - 8.1. Open-Loop Motion of One Joint. - 8.2. Open-Loop Motion of Three Joints. - 8.3. Friction Compensated Force Control. - 9. Suggestions Toward Friction Modeling and Compensation. - 9.1. Suggestions on Experimental Technique. - 9.2. Suggestions on Control. - 9.3. Conclusion. - Appendix A: Small Studies. - A.1 Friction as a Function of Motor Angle. - A.2 Joint 2 Motor Alone and Joint 2 Link Alone. - A.3 Trials with Dither. - A.4 Friction as a Function of Load. - A.5 Creep. - A.6 Effects that were not Observed.
RNA-Binding Proteins in Plant Immunity

Plant defence responses against pathogen infection are crucial to plant survival. The high degree of regulation of plant immunity occurs both transcriptionally and posttranscriptionally. Once transcribed, target gene RNA must be processed prior to translation. This includes polyadenylation, 5′capping, editing, splicing, and mRNA export. RNA-binding proteins (RBPs) have been implicated at each level of RNA processing. Previous research has primarily focused on structural RNA-binding proteins of yeast and mammals; however, more recent work has characterized a number of plant RBPs and revealed their roles in plant immune responses. This paper provides an update on the known functions of RBPs in plant immune response regulation. Future in-depth analysis of RBPs and other related players will unveil the sophisticated regulatory mechanisms of RNA processing during plant immune responses.
Automatic segmentation of clustered breast cancer cells using watershed and concave vertex graph

Automatic segmentation of stained breast tissue images helps pathologists to discover the cancer disease earlier. Separation of touching cells presents many difficulties to the traditional segmentation algorithms. In this paper, we propose a new automatic method to segment clustered cancer cells. In the first step, we detect cell regions using a modified geometric active contour based on Chan-Vese energy functional. Then, touching cell regions are extracted from the pre-segmented image by detecting high concavity points along the cell contours. A gradient-weighted distance transform is used in the watershed algorithm in order to get the most significant inner edges. To solve the problem of over-segmentation, which is the major drawback of the watershed method, a combination of three techniques is presented as a post-processing step. First, the nearest end points to concave vertices are detected in the inner edges in order to get the initial separating curve candidates. Second, a concave vertex graph is constructed from the end points and the separating curves. Finally, Dijkstra algorithm is applied to find the shortest path that separates the touching cells. The proposed algorithm is tested on several breast cancer cell images and it's compared with the classical watershed algorithm and a recent marker-controlled watershed method. The experimental results show the performance of the presented approach.
A Prioritized Multiprocessor Spin Lock

In this paper, we present the PR lock, a prioritized spin lock mutual exclusion algorithm. The PR lock is a contention-free spin lock, in which blocked processes spin on locally stored or cached variables. In contrast to previous work on prioritized spin locks, our algorithm maintains a pointer to the lock holder. As a result, our spin lock can support operations on the lock holder (e.g., for abort ceiling protocols). Unlike previous algorithms, all work to maintain a priority queue is done while a process acquires a lock when it is blocked anyway. Releasing a lock is a constant time operation. We present simulation results that demonstrate the prioritized acquisition of locks, and compare the performance of the PR lock against that of the best alternative prioritized spin lock.
Information Filtering against Information Pollution and Crime

With the development and increasing popularity of information technology, how to effectively receive and manage the information from the Internet becomes a more pronounced problem. According to certain standards, users can take some methods of information filtering to block the information they do not want and retrieve the information they want. In this way, people can effectively avoid false information, spam, commercial advertising, insulting, Internet attacks, pornography, and other internet problems. This paper focuses on information filtering systems against information pollution and crime, describes the characteristics and methods of information filtering, and introduces some information filtering software.
The impact of load on lower body performance variables during the hang power clean

This study examined the impact of load on lower body performance variables during the hang power clean. Fourteen men performed the hang power clean at loads of 30%, 45%, 65%, and 80% 1RM. Peak force, velocity, power, force at peak power, velocity at peak power, and rate of force development were compared at each load. The greatest peak force occurred at 80% 1RM. Peak force at 30% 1RM was statistically lower than peak force at 45% (p = 0.022), 65% (p = 0.010), and 80% 1RM (p = 0.018). Force at peak power at 65% and 80% 1RM was statistically greater than force at peak power at 30% (p < 0.01) and 45% 1RM (p < 0.01). The greatest rate of force development occurred at 30% 1RM, but was not statistically different from the rate of force development at 45%, 65%, and 80% 1RM. The rate of force development at 65% 1RM was statistically greater than the rate of force development at 80% 1RM (p = 0.035). No other statistical differences existed in any variable existed. Changes in load affected the peak force, force at peak power, and rate of force development, but not the peak velocity, power, or velocity at peak power.
Performance Analysis of Orthogonal Pairs Designed for an Expanded Eukaryotic Genetic Code

Background The suppression of amber stop codons with non-canonical amino acids (ncAAs) is used for the site-specific introduction of many unusual functions into proteins. Specific orthogonal aminoacyl-tRNA synthetase (o-aaRS)/amber suppressor tRNACUA pairs (o-pairs) for the incorporation of ncAAs in S. cerevisiae were previously selected from an E. coli tyrosyl-tRNA synthetase/tRNACUA mutant library. Incorporation fidelity relies on the specificity of the o-aaRSs for their ncAAs and the ability to effectively discriminate against their natural substrate Tyr or any other canonical amino acid. Methodology/Principal Findings We used o-pairs previously developed for ncAAs carrying reactive alkyne-, azido-, or photocrosslinker side chains to suppress an amber mutant of human superoxide dismutase 1 in S. cerevisiae. We found worse incorporation efficiencies of the alkyne- and the photocrosslinker ncAAs than reported earlier. In our hands, amber suppression with the ncAA containing the azido group did not occur at all. In addition to the incorporation experiments in S. cerevisiae, we analyzed the catalytic properties of the o-aaRSs in vitro. Surprisingly, all o-aaRSs showed much higher preference for their natural substrate Tyr than for any of the tested ncAAs. While it is unclear why efficiently recognized Tyr is not inserted at amber codons, we speculate that metabolically inert ncAAs accumulate in the cell, and for this reason they are incorporated despite being weak substrates for the o-aaRSs. Conclusions/Significance O-pairs have been developed for a whole plethora of ncAAs. However, a systematic and detailed analysis of their catalytic properties is still missing. Our study provides a comprehensive scrutiny of o-pairs developed for the site-specific incorporation of reactive ncAAs in S. cerevisiae. It suggests that future development of o-pairs as efficient biotechnological tools will greatly benefit from sound characterization in vivo and in vitro in parallel to monitoring intracellular ncAA levels.
ICA-Based EEG Classification Using Fuzzy C-mean Algorithm

In this paper we used Independent Component Analysis (ICA) model of EEG signals for preprocessing and then Discrete Wavelet Transform (DWT) analysis for feature extraction from EEG signal which this features are useful in BCI application. Then we used Fuzzy C-means (FCM) algorithm for recognition of some diseases like epileptic seizure, Cerebral Palsy (CP), etc. This project can be divided in three parts. The first part is EEG signal preprocessing using ICA. The second part is the feature extraction of normal and abnormal EEG using feature vectors derived from the wavelet analysis. The third part is the classification of normal and abnormal signals using FCM algorithm. In section II we explain EEG signal preprocessing, in section III we describe feature extraction and in section IV we explain the classification
Managing the Charging of Electrical Vehicles: Impacts on the Electrical Grid and on the Environment

Electric vehicles are seen as an option to reduce greenhouse emissions, directly related with the electricity generation mix and with the time of charging due to the variations of the generation sources during the day. At the same time, with their widespread adoption the increase in the demand for electricity to charge these vehicles could pose significant challenges to the electrical grid in terms of additional load due to unmanaged charge strategies. In order to mitigate these problems, the charging of the electrical vehicles must be managed. This paper presents the development of a system architecture to dynamically control the charging of electric vehicles to maintain the proper operation of the local distribution grid and minimize the environmental impact. The hardware consists of two modules, a meter and controllable plugs both with communication capabilities, while the software consists in a forecast and scheduler module. The forecast module calculates the load based on the power consumption behavior and uses the renewable generation forecast to assign the best time slot to charge the vehicle. The system aims to minimize the load peaks and flatten the load profile, while minimizing the environmental impacts. Based on the user preferences, system characteristics, consumption and renewable generation forecast, the system will assign the most suitable time slot to charge the electric vehicle. For the case of multiple electric vehicles, the system will schedule their charge based on a calculated priority level, in order to maintain a reliable operation of the local electrical grid.
Secure computation of surveys

We describe the design and implementation of a system for conducting surveys while hiding the information provided by the respondents. We use the CRA Taulbee Survey of faculty salaries in computer science departments as a concrete example in which there are real privacy concerns but in which participation is too large and uncoordinated for direct application of known secure multiparty function evaluation protocols. Our system extends earlier work considering privacy in auctions. We adopt the approach of designating a small number of parties to do the main secure computation, but we go farther in addressing the reality of haphazard input arrival, and possible non-arrival, so that “the function,” in the usual sense, is not known until it is decided at some point to cease collecting inputs, at which point the participants at large—humans and machines—cannot be expected to be available for any interaction. A major impediment to acceptance of secure-function-evaluation technology in practice is the fundamental incompatibility of privacy preservation without trusted parties with “sanity checking” of inputs. For the CRA Taulbee Survey, we show that a reasonable partial remedy is possible. 1 Surveys and Privacy The term survey can reasonably and usefully be taken to be quite general, subsuming referenda, elections (“Whom would you prefer in office? ”), and sealed-bid auctions (“How much would you be willing to pay? ”). A survey solicits of participants information to which they have privileged access so that this information may be fed into some computation whose result is of interest to the conductor of the survey and, possibly also, at least in some indirect fashion and to some degree, to the participants. The participants’ privileged access to the information asked of them may occasion concern regarding loss of privacy in revelation or may not at all; the perceived penalty for participation is as apt to be the required investment of time and effort. Surveys vary no less in their payoff aspect. The participant may gain no more than the satisfaction of manifesting a spirit of cooperation; or, as in a referendum or an election or an auction, the participant may have a clear stake in the result of the “survey” computation, which he would wish to modulate through participation. This work was supported by the DoD University Research Initiative (URI) administered by the Office of Naval Research. †Supported in part by ONR grant N00014-01-1-0795 and NSF grant ITR-0331548. ‡Supported by ONR grant N00014-01-1-0795 and US-Israel BSF grant 2002065. §Supported by US-Israel BSF grant 2002065 and ONR grant N00014-04-1-0725.