Miracle-dz/UniFAR-FTUs huggingface dataset:
A Symbolic Representation Approach for the Diagnosis of Broken Rotor Bars in Induction Motors

One of the most common deficiencies of currently existing induction motor fault diagnosis techniques is their lack of automatization. Many of them rely on the qualitative interpretation of the results, a fact that requires significant user expertise, and that makes their implementation in portable condition monitoring devices difficult. In this paper, we present an automated method for the detection of the number of broken bars of an induction motor. The method is based on the transient analysis of the start-up current using wavelet approximation signal that isolates a characteristic component that emerges once a rotor bar is broken. After the isolation of this component, a number of stages are applied that transform the continuous-valued signal into a discrete one. Subsequently, an intelligent icon-like approach is applied for condensing the relative information into a representation that can be easily manipulated by a nearest neighbor classifier. The approach is tested using simulation as well as experimental data, achieving high-classification accuracy.
Addiction and volition in problematic Internet use among college students

by Cody D. Christopherson Exclusive use of the paradigm of mechanistic determination may be inappropriate for the systematic study of human beings in psychology. There have been some studies that have attempted to use a framework which makes teleological explanations possible while maintaining scientific empirical rigor. This type of study could prove especially helpful in the fields where the existence of volitional control for a particular behavior is debated. Internet use and abuse is such a field. Addiction, or lack of volitional control, is central to the fervor over Internet use and mental health. Internet use is also a field which has rarely been studied empirically. Using a relatively new teleological methodology, Internet use is shown to be a volitional behavior for most members of a non-clinical population. Participants were assessed according to a battery of Internet addiction scales to determine which, if any, of the tests can predict lack of volitional control of Internet use. No test was able to reliably predict lack of volitional control.
An OmpA Family Protein, a Target of the GinI/GinR Quorum-Sensing System in Gluconacetobacter intermedius, Controls Acetic Acid Fermentation

ABSTRACT Via N-acylhomoserine lactones, the GinI/GinR quorum-sensing system in Gluconacetobacter intermedius NCI1051, a gram-negative acetic acid bacterium, represses acetic acid and gluconic acid fermentation. Two-dimensional polyacrylamide gel electrophoretic analysis of protein profiles of strain NCI1051 and ginI and ginR mutants identified a protein that was produced in response to the GinI/GinR regulatory system. Cloning and nucleotide sequencing of the gene encoding this protein revealed that it encoded an OmpA family protein, named GmpA. gmpA was a member of the gene cluster containing three adjacent homologous genes, gmpA to gmpC, the organization of which appeared to be unique to vinegar producers, including “Gluconacetobacter polyoxogenes. ” In addition, GmpA was unique among the OmpA family proteins in that its N-terminal membrane domain forming eight antiparallel transmembrane β-strands contained an extra sequence in one of the surface-exposed loops. Transcriptional analysis showed that only gmpA of the three adjacent gmp genes was activated by the GinI/GinR quorum-sensing system. However, gmpA was not controlled directly by GinR but was controlled by an 89-amino-acid protein, GinA, a target of this quorum-sensing system. A gmpA mutant grew more rapidly in the presence of 2% (vol/vol) ethanol and accumulated acetic acid and gluconic acid in greater final yields than strain NCI1051. Thus, GmpA plays a role in repressing oxidative fermentation, including acetic acid fermentation, which is unique to acetic acid bacteria and allows ATP synthesis via ethanol oxidation. Consistent with the involvement of gmpA in oxidative fermentation, its transcription was also enhanced by ethanol and acetic acid.
Density evolution analysis of braided convolutional codes on the erasure channel

Braided convolutional codes (BCCs) are a class of spatially coupled turbo-like codes with a structure that is similar to product codes or generalized LDPC codes. We derive explicit input/output transfer functions of the component convolutional decoders for the binary erasure channel (BEC). These are then used to formulate exact density evolution equations for blockwise BCCs under belief propagation (BP) decoding with optimal component APP decoders. Thresholds are computed for the coupled and uncoupled case, which is equivalent to tailbiting. Due to the relatively high rate of the component codes a significant threshold improvement by spatial coupling can be observed.
Uniform density theorem for the Hubbard model

A general class of hopping models on a finite bipartite lattice is considered, including the Hubbard model and the Falicov–Kimball model. For the half‐filled band, the single‐particle density matrix ρ(x,y) in the ground state and in the canonical and grand canonical ensembles is shown to be constant on the diagonal x=y, and to vanish if x≠y and if x and y are on the same sublattice. For free electron hopping models, it is shown in addition that there are no correlations between sites of the same sublattice in any higher order density matrix. Physical implications are discussed.
Eukaryotic LYR Proteins Interact with Mitochondrial Protein Complexes

In eukaryotic cells, mitochondria host ancient essential bioenergetic and biosynthetic pathways. LYR (leucine/tyrosine/arginine) motif proteins (LYRMs) of the Complex1_LYR-like superfamily interact with protein complexes of bacterial origin. Many LYR proteins function as extra subunits (LYRM3 and LYRM6) or novel assembly factors (LYRM7, LYRM8, ACN9 and FMC1) of the oxidative phosphorylation (OXPHOS) core complexes. Structural insights into complex I accessory subunits LYRM6 and LYRM3 have been provided by analyses of EM and X-ray structures of complex I from bovine and the yeast Yarrowia lipolytica, respectively. Combined structural and biochemical studies revealed that LYRM6 resides at the matrix arm close to the ubiquinone reduction site. For LYRM3, a position at the distal proton-pumping membrane arm facing the matrix space is suggested. Both LYRMs are supposed to anchor an acyl-carrier protein (ACPM) independently to complex I. The function of this duplicated protein interaction of ACPM with respiratory complex I is still unknown. Analysis of protein-protein interaction screens, genetic analyses and predicted multi-domain LYRMs offer further clues on an interaction network and adaptor-like function of LYR proteins in mitochondria.
Enhancing Environmental Surveillance Against Organised Crime with Radial Basis Neural Networks

A huge amount of data concerning the position of individual is often gathered in surveillance scenarios, to prevent crimes or to collect evidence of unlawful behaviour. Given the abundance of data available, detectives need advanced analysis means in order to set apart the interesting locations. This paper proposes a solution that makes use of radial basis neural networks to find the points of interests, i.e. Locations that have been used for meeting, for surveilled people whose paths have been traced. In our solution newly gathered data will be analysed in order to find points of interest, and will also be given to our neural network for further training. Our results show that the proposed approach is accurate enough and can improve the unaided search for meeting points between observed individuals.
Cytobots: intracellular robotic micromanipulators

A cytobot is an intracellular robotic micromanipulator, a microfabricated device small enough to be introduced into a cell. Control for a cytobot can be accomplished using three mutually perpendicular sequential magnetic control systems along with an electromechanical stepper microscope stage. Control depends on viscous damping within the cell. The design and fabrication techniques are discussed and the processing techniques used in the fabrication of cytobots highlighted. Fabrication of various magnetic cytobots are then illustrated namely, a chisel, a "circular" saw blade, a "fishing" hook; a cuff for fibers, a box to confine an organelle, and an aspirator, and the functionality of these devices is explained. In order for the cytobot to get into the cell, it must be injected with a small needle, or since the majority of the structure is a magnet, it could be fired in ballisticly like a magnetic bullet. Once introduced into an embryonic cell one can continuously manipulate one cell of the developing organism as cell division proceeds. We also discuss the possibility of making such devices small enough to enter the cell nucleus, i.e., karyobots.
Comment on ''Heat capacity, time constant, and sensitivity of Earth's climate system'' by S. E. Schwartz

[1] In a recent paper, Schwartz [2007] (hereinafter referred to as S07) estimated climate sensitivity using globally averaged observed time series. He estimated the planet’s effective heat capacity and ‘‘pertinent time constant’’ from ocean heat content and observed global temperature records, assuming that the latter can be modeled as a firstorder Markov (AR(1)) process after removing the trend due to climate forcing by subtracting a linear trend. [2] As S07 correctly states, the autocorrelation of an AR(1) process at lag Dt follows the simple relation
Incremental dependency parsing based on headed context-free grammar

This paper proposes the incremental dependency parsing method based on the context-free grammar with dependency information. In the proposed method, the reachability, which represents the relation between categories, is used. In parallel to the inputting of sentence, the dependency, which is the relation between the modifying word and the modified word, is computed. In the proposed method, the parse tree to cover the inputted fragment of the sentence is not needed. Consequently, the method can compute the dependency more efficiently than the method that computes the dependency from the parse tree. As a result of a parsing experiment using ATIS corpus, the proposed method utilizing the reachability is demonstrated to be effective in reducing the parsing time. © 2005 Wiley Periodicals, Inc. Syst Comp Jpn, 36(2): 63–77, 2005; Published online in Wiley InterScience (www.interscience. wiley.com). DOI 10.1002/scj.10524
Secure hybrid digital-analog Wyner-Ziv coding

In this work, the problem of transmitting an i.i. d Gaussian source over an i.i. d Gaussian wiretap channel with an i.i. d Gaussian side information at the intended receiver is considered. The intended receiver is assumed to have a certain minimum SNR and the eavesdropper is assumed to have a strictly lower SNR compared to the intended receiver. The objective is minimizing the distortion of source reconstruction at the intended receiver. In this work, it is shown that the source-channel separation coding scheme is optimum in the sense of achieving the minimum distortion. A hybrid digital-analog Wyner-Ziv coding scheme is then proposed which achieve the minimum distortion. This secure joint source channel coding scheme is based on Wyner-Ziv coding scheme and wiretap channel coding scheme when the analog source is not explicitly quantized. The proposed secure hybrid digital-analog scheme is analyzed under the main channel SNR mismatch. It is proven that the proposed scheme can give a graceful degradation of distortion with SNR under SNR mismatch, i.e., when the actual SNR is larger than the designed SNR.
A One-Parameter Structure for Adaptive Iterative Learning Control of Robot Manipulators

In this paper, a new one-parameter structure is presented for the design of adaptive iterative learning controller for repetitive control of robot manipulators. Only one control parameter is needed for compensation of the unknown plant information so that the size of memory for storage of previous control information can be greatly reduced. In addition to the new control structure, an adaptive algorithm combining time-domain and iteration-domain adaptation is also proposed. The combined adaptive law can relax the requirement of certain unknown upper bound usually used in current existing adaptive iterative learning control schemes. The technical analysis shows that the boundedness of all the internal signals and convergence of the learning error are guaranteed without using projection mechanism in adaptive laws. Finally, a simulation result is provided to illustrate the effectiveness of the learning controller.
Hepatoprotective, Antioxidant, and Anticancer Effects of the Tragopogon porrifolius Methanolic Extract

Tragopogon porrifolius (Asteraceae), commonly referred to as white salsify, is an edible herb used in Lebanese folk medicine to treat cancer and liver dysfunction. In this study, we investigated the antioxidant activity of Tragopogon porrifolius methanolic extract, both in vitro and in vivo, in addition to its hepatoprotective and anticancer activities. Total phenolic and flavonoid contents were measured and found to be 37.0 ± 1.40 mg GAE/g and 16.6 ± 0.42 mg QE/g dry weight, respectively. In vitro antioxidant assays revealed an FRAP value of 659 ± 13.8 µmol Fe2+/g of extract and DPPH IC50 value 15.2 µg/mL. In rats subjected to CCl4-induced hepatotoxicity, significant increase in CAT, SOD, and GST levels was detected. The highest dose of the extract (250 mg/kg) recorded a fold increase of 1.68 for SOD, 2.49 for GST, and 3.2 for CAT. The extract also showed substantial decrease in AST (57%), ALT (56%), and LDH (65%) levels. Additionally, the extract caused a dose-dependent decrease in cell viability and proliferation. In conclusion, the methanolic extract of T. porrifolius displayed a relatively high antioxidant activity both in vitro and in vivo as well as hepatoprotective potential against liver toxicity in rats and anticancer effect on MDA-MB-231 and Caco-2 cells.
Oxygen concentration during mouse oocyte in vitro maturation affects embryo and fetal development.

BACKGROUND Little is known of how the oxygen environment in the ovarian follicle affects oocyte and embryo development, but this has an important impact on the conditions used for in vitro maturation (IVM) of oocytes. We investigated the effect of varying oxygen concentrations during IVM on subsequent pre and post-implantation development. METHODS IVM of mouse cumulus-oocyte complexes (COCs) was performed under 2, 5, 10 or 20% O(2) (6% CO(2), balance N(2)). In vivo-matured COCs were collected post ovulation. Embryos were generated by IVF and culture. Blastocyst development, cell number and apoptosis were assessed, and fetal and placental outcomes analysed following embryo transfer at day 18 of pregnancy. RESULTS Oxygen concentration during IVM did not affect oocyte maturation or subsequent fertilization, cleavage and blastocyst development rates. Maturation of oocytes under 2% O(2) increased blastocyst trophectoderm cell number compared with all groups and numbers at 5% were higher than 20% (both P < 0.05). Percentage of apoptotic cells was increased in blastocysts developed from 2% O(2)-matured oocytes, compared with maturation at 5% O(2) or in vivo (P < 0.05). Rates of embryo implantation and development into a viable fetus were not altered by IVM oxygen. However, fetal weight was reduced following oocyte maturation at 5% O(2) compared wiht 20% O(2) and maturation at 5% O(2) also reduced placental weight, when compared with in vivo-matured oocytes (both P < 0.05). CONCLUSIONS Level of O(2) exposure during oocyte maturation can alter the cellular composition of blastocysts, but these changes in cell number do not correlate with the altered fetal and placental outcomes after transfer.
Rapid and generalized identification of packetized voice traffic flows

In this paper we describe the construction and performance of classifiers able to identify Variable Rate VoIP traffic flows rapidly, reliably and independently of the application version that generated it. We show that features calculated on short sequences of packets extracted from the flow (sub-flows) are sufficient to identify VoIP flows with Recall of 99% and Precision of 90%. The features we used are based on mean packet length, autocorrelation and the ratio of data transmitted in either direction of a bi-directional flow. Even though the codecs we use to generate VoIP traffic are quite different, we show that by using selected features that capture the nature of variable bit rate voice traffic, a classifier trained on traffic generated by one version of VoIP can reliably recognize traffic generated by another version.
Stochastic Optimization , Tree Structures and Portfolio Choice

Solving realistic dynamic asset allocation problems remains a challenge. While considerable progress with respect to theoretical insights has been made in the past years using dynamic programming, this technique is hardly applicable to deal with industry problems involving numerous sources of uncertainty and path-dependent variables. An alternative solution strategy that has been applied to various applications in finance is Stochastic Linear Programming (SLP). However, what is missing in the literature so far is an extensive evaluation of the influence of different parameters that have to be determined before solving a SLP, namely the tree structure and the procedure of scenario generation. In this paper, we perform such an analysis by setting up an artificial portfolio management problem whose theoretical optimal solution is known. Therefore we can evaluate the accuracy of solutions derived via SLP against this known benchmark. We find that the tree structure plays an important role as long as simple scenario generation techniques are concerned. For sophisticated techniques, which ensure that even for a small number of random draws the first two moments of the distribution are matched, the scenario tree structure is less important. However, for simple Monte Carlo techniques – used in most of the existing research papers – the tree structure might considerably bias the optimal solutions. In such situations, symmetric trees (e.g., 100x100) show best performance.
Arabidopsis thaliana telomeric DNA-binding protein 1 is required for telomere length homeostasis and its Myb-extension domain stabilizes plant telomeric DNA binding

Telomeres are specific protein–DNA complexes that protect the ends of eukaryotic chromosomes from fusion and degradation and are maintained by a specialized mechanism exerted by telomerase and telomere-binding proteins (TBPs), which are evolutionarily conserved. AtTBP1 is an Arabidopsis thaliana protein that binds plant telomeric DNA in vitro. Here, we demonstrated that lack of AtTBP1 results in a deregulation of telomere length control, with mutant telomeres expanding steadily by the fourth generation. DNA-binding studies with mutant AtTBP1 proteins showed that the Myb-extension domain of AtTBP1 is required for binding to plant telomeric DNA. Our results suggest that AtTBP1 is involved in the telomere length mechanism in A. thaliana and that the Myb-extension domain of AtTBP1 may stabilize plant telomeric DNA binding.
Fusion of map matching and traffic sign recognition

This paper presents a high performance and robust system for traffic sign recognition with digital map fusion. The proposed system is enhanced by fusion of different sensors and recognition is improved. Traffic sign is detected by a monochrome camera added by a reflective surface detector whereas recognition is achieved by a template matching algorithm. Digital Maps used in this work are standard navigable data. For localization the GPS receiver and the odometer of the test vehicle is used with the developed particle filter based map-matching algorithm. Tests are accomplished in rural and urban areas of metropolitan city for both day and night conditions. Especially, success rate at night scenes is comparably higher when compared to existing approaches and technologies. The system is unique since it is not limited to certain sign types, can be used in day and night conditions. The proposed system can be easily adapted to real world applications since it utilizes low cost and industrially available digital map content and sensors.
An efficient method to identify differentially expressed genes in microarray experiments

MOTIVATION Microarray experiments typically analyze thousands to tens of thousands of genes from small numbers of biological replicates. The fact that genes are normally expressed in functionally relevant patterns suggests that gene-expression data can be stratified and clustered into relatively homogenous groups. Cluster-wise dimensionality reduction should make it feasible to improve screening power while minimizing information loss. RESULTS We propose a powerful and computationally simple method for finding differentially expressed genes in small microarray experiments. The method incorporates a novel stratification-based tight clustering algorithm, principal component analysis and information pooling. Comprehensive simulations show that our method is substantially more powerful than the popular SAM and eBayes approaches. We applied the method to three real microarray datasets: one from a Populus nitrogen stress experiment with 3 biological replicates; and two from public microarray datasets of human cancers with 10 to 40 biological replicates. In all three analyses, our method proved more robust than the popular alternatives for identification of differentially expressed genes. AVAILABILITY The C++ code to implement the proposed method is available upon request for academic use.
Peer to Peer Video on Demand Architecture using V-Chaining

In the Internet, video streaming requires greater amount of network bandwidth and other resources as the number of user requests increases. In case of traditional centralized directory server approach all the users requests are directly handled by the centralized server and each user request will send dedicated stream by the server, which requires higher end server, server cost will become more and greater amount of network bandwidth utilized by this server. To solve these problems peer to peer technology as emerged for the distribution of video streams to the larger requests over the network. In P2P VoD architecture adopted both the peer to peer and proxy based architectural design of a VOD system for larger community of users over the network. Hence our proposed Peer to Peer Video on Demand Architecture using V-Chaining improves the overall performance of the system by efficient utilization of uplink bandwidth and smaller amount of buffer space among the peers. In this paper we have introduce architecture for handle the large number of user requests over the communication network and ease of implementation.
On Detecting Messaging Abuse in Short Text Messages using Linguistic and Behavioral patterns

The use of short text messages in social media and instant messaging has become a popular communication channel during the last years. This rising popularity has caused an increment in messaging threats such as spam, phishing or malware as well as other threats. The processing of these short text message threats could pose additional challenges such as the presence of lexical variants, SMS-like contractions or advanced obfuscations which can degrade the performance of traditional filtering solutions. By using a real-world SMS data set from a large telecommunications operator from the US and a social media corpus, in this paper we analyze the effectiveness of machine learning filters based on linguistic and behavioral patterns in order to detect short text spam and abusive users in the network. We have also explored different ways to deal with short text message challenges such as tokenization and entity detection by using text normalization and substring clustering techniques. The obtained results show the validity of the proposed solution by enhancing baseline approaches.