Miracle-dz/UniFAR-FTUs huggingface dataset:
Isolation of acholeplasmas and a mycoplasma from vegetables

The isolation of Mollicutes from food has not been reported. To isolate Mollicutes in the presence of high levels of unwanted bacteria, we first incubated fresh vegetables in liquid culture media containing lysozyme, ampicillin, and thallous acetate. Culture fluids were than separated from the vegetable samples, subjected to one freeze-thaw cycle, and passed through a filter of 0.4-micron porosity. Filtered samples were cultured in SP4 medium and in a conventional medium containing horse serum. With this procedure 21 acholeplasma isolations representing three species were obtained from endive, broccoli, and kale. Of 35 food samples tested, 11 were positive for acholeplasmas; acholeplasmas isolated from 6 of these samples were recovered only in SP4 medium. In seven single vegetable samples, two or more Acholeplasma spp. were isolated. A. laidlawii was isolated from all three vegetables and A. axanthum was found in broccoli and kale. Four isolates were serologically identified as A. oculi. Mycoplasma verecundum was the only Mycoplasma species recovered. Several isolates could not be typed serologically, as they reacted with antisera to both A. morum and A. hippikon. these isolates may include new Acholeplasma spp.
Evaluation of the effect of food and beverages on enamel and restorative materials by SEM and Fourier transform infrared spectroscopy

Objectives To examine different types of restorative materials used in children as well as primary and permanent teeth enamel when affected by erosive foods. Materials and Method Buttermilk, fruit yoghurt, Coca‐cola, fruit juice, Filtek Z‐250, Dyract Extra, Fuji II LC, and Fuji IX and tooth enamel were used. Measurements were performed on 1‐day, 1‐week, 1‐month, 3‐month, 6‐month time periods by using ATR‐FTIR technique and surface of the specimens were examined with SEM. Results Permanent tooth showed the least change among human tooth samples when compared to restorative materials. Among filler materials, the most change was observed in Fuji IX. In terms of beverages the most changes on absorption peaks obtained from spectra were seen on the samples held in Coca‐Cola and orange‐juice. Conclusion The exposure of human enamel and restorative materials to acidic drinks may accelerate the degradation process and so reduce the life time of filler materials at equivalent integral exposure times longer than three months. Clinical Relevance Erosive foods and drinks having acidic potential destroy not only tooth enamel but also restorative materials. Microsc. Res. Tech. 77:79–90, 2014. © 2013 Wiley Periodicals, Inc.
Intra-Cluster Characteristics of 28 GHz Wireless Channel in Urban Micro Street Canyon

Abstract-This paper investigates intra-cluster channel characteristics of non line-of-sight (NLOS) 28 GHz channels in street canyon scenarios. These channel characteristics include cluster numbers, number of subpaths within each cluster, intra-cluster delay spreads, and intra-cluster angular spreads. Both measurement and ray tracing results are presented and compared. Furthermore, distribution fittings are performed and models and parameters for different intra-cluster channel characteristics are proposed.
Design-oriented estimation of thermal noise in switched-capacitor circuits

Thermal noise represents a major limitation on the performance of most electronic circuits. It is particularly important in switched circuits, such as the switched-capacitor (SC) filters widely used in mixed-mode CMOS integrated circuits. In these circuits, switching introduces a boost in the power spectral density of the thermal noise due to aliasing. Unfortunately, even though the theory of noise in SC circuits is discussed in the literature, it is very intricate. The numerical calculation of noise in switched circuits is very tedious, and requires highly sophisticated and not widely available software. The purpose of this paper is twofold. It provides a tutorial description of the physical phenomena taking place in an SC circuit while it processes noise (Sections II-III). It also proposes some specialized but highly efficient algorithms for estimating the resulting sampled noise in SC circuits, which need only simple calculations (Sections IV-VI ). A practical design procedure, which follows directly from the estimate, is also described. The accuracy of the proposed estimation algorithms is verified by simulation using SpectreRF. As an example, it is applied to the estimation of the total thermal noise in a second-order low-distortion delta-sigma converter.
A novel switched compensation controller for multi-link flexible manipulators

We present a novel control algorithm for multi-link flexible planar manipulators. The proposed scheme is a switching rule between a new nonlinear controller and a conventional PD (proportional and derivative) controller. We prove the stability of the controller using La Salle's theorem. Simulation results illustrate the improvement over PD controller.
THE SPLITTING OF HEPATOCYTE GAP JUNCTIONS AND ZONULAE OCCLUDENTES WITH HYPERTONIC DISACCHARIDES

Mouse livers were perfused in situ through the portal vein with the disaccharides sucrose, lactose, maltose, and cellobiose in hypertonic concentrations (0.5 M). This treatment resulted in plasmolysis of the hepatocytes and splitting of the gap junctions and zonulae occludentes. The junctions split symmetrically, leaving a half-junction on each of the two separated cells. The process of junction splitting is followed using the freeze-fracture technique, since the junctional membranes are indistinguishable from the nonjunctional membranes in thin sections once the splitting occurs. The split junctions are also studied using the freeze-etch technique, allowing a view of the gap junction extracellular surface normally sequestered within the 2-nm "gap. " The monosaccharides sorbitol and mannitol did not split the junctions during the times studied (2 min), but substitution of the chloride ion with propionate in the perfusion mixture did result in junction splitting. An envelope of morphologically distinct particles surrounding freeze-fractured gap junctions is also described.
DFCM: Density Based Approach to Identify Outliers and to Get Efficient Clusters in Fuzzy Clustering

The task of outlier identification is to find small groups of data objects that are exceptional when compared with rest large amount of data. The identification of outliers can lead to the discovery of truly unexpected knowledge in areas such as electronic commerce, credit card frauds, voting irregularity analysis, data cleansing, network intrusion, severe weather prediction & many more. This paper deals with the identification of outliers and to get efficient clusters in fuzzy clustering. In this paper a new density based definition of outlier and an algorithm dasiaDFCMpsila is proposed; which works in two phases. In first phase, it identifies outliers and separate them from original data-set and in the second phase, it creates clusters from noiseless data. DFCM modifies FCM fuzzy clustering technique to create clusters. But it can also be implemented with any other fuzzy clustering technique. Numerical examples and tests show that proposed algorithm gives better result when compared with FCM.
A fully integrated fully differential low-noise amplifier for short range automotive radar using a SiGe:C BiCMOS Technology

A fully integrated fully differential low-noise amplifier for 79 GHz short range radar applications using a highspeed SiGe:C BiCMOS technology is presented. The integrated circuit uses thin-film microstrip lines and exhibits compact design (530 times 690 mum2), low power consumption (90 mW at 3 V supply voltage), high gain (13 dB gain at 81 GHz), good linearity and reverse isolation. In order to ease the measurements of the circuit, a simple technique was used to measure single-ended the differential amplifier. To overcome possible inaccuracy of the line model, shorting bars are placed along these elements to allow easy correction and to avoid redesign.
Single Cell Stochastic Regulation of Pilus Phase Variation by an Attenuation-like Mechanism

The molecular triggers leading to virulence of a number of human-adapted commensal bacteria such as Streptococcus gallolyticus are largely unknown. This opportunistic pathogen is responsible for endocarditis in the elderly and associated with colorectal cancer. Colonization of damaged host tissues with exposed collagen, such as cardiac valves and pre-cancerous polyps, is mediated by appendages referred to as Pil1 pili. Populations of S. gallolyticus are heterogeneous with the majority of cells weakly piliated while a smaller fraction is hyper piliated. We provide genetic evidences that heterogeneous pil1 expression depends on a phase variation mechanism involving addition/deletion of GCAGA repeats that modifies the length of an upstream leader peptide. Synthesis of longer leader peptides potentiates the transcription of the pil1 genes through ribosome-induced destabilization of a premature stem-loop transcription terminator. This study describes, at the molecular level, a new regulatory mechanism combining phase variation in a leader peptide-encoding gene and transcription attenuation. This simple and robust mechanism controls a stochastic heterogeneous pilus expression, which is important for evading the host immune system while ensuring optimal tissue colonization.
Malaysian Vehicle License Plate Recognition

Vehicle license plate recognition is an image-processing technology used to identify vehicles by their license plates. This technology can be used in various security and traffic applications, such as finding stolen cars, controlling access to car parks and gathering traffic flow statistics. In this paper an approach to license plate localization and recognition is presented. A proposed method to perform recognition of license plates under any environmental conditions, with no assumptions about the orientation of the plate or its distance from the camera is designed. To solve the problem of localization of a license plate, a simple texture-based approach based on edge information is used. Segmentation of characters is performed by using connected components analysis on license plate’s image, and a simple multi-layer Perceptron neural network is used to recognize them. Simulation results were shown to be an efficient method for real time plate recognition.
“Search, Show Context, Expand on Demand”: Supporting Large Graph Exploration with Degree-of-Interest

A common goal in graph visualization research is the design of novel techniques for displaying an overview of an entire graph. However, there are many situations where such an overview is not relevant or practical for users, as analyzing the global structure may not be related to the main task of the users that have semi-specific information needs. Furthermore, users accessing large graph databases through an online connection or users running on less powerful (mobile) hardware simply do not have the resources needed to compute these overviews. In this paper, we advocate an interaction model that allows users to remotely browse the immediate context graph around a specific node of interest. We show how Furnas' original degree of interest function can be adapted from trees to graphs and how we can use this metric to extract useful contextual subgraphs, control the complexity of the generated visualization and direct users to interesting datapoints in the context. We demonstrate the effectiveness of our approach with an exploration of a dense online database containing over 3 million legal citations.
Dissemination of Drinking Water Contamination Data to Consumers: A Systematic Review of Impact on Consumer Behaviors

Background Drinking water contaminated by chemicals or pathogens is a major public health threat in the developing world. Responses to this threat often require water consumers (households or communities) to improve their own management or treatment of water. One approach hypothesized to increase such positive behaviors is increasing knowledge of the risks of unsafe water through the dissemination of water contamination data. This paper reviews the evidence for this approach in changing behavior and subsequent health outcomes. Methods/Principal Findings A systematic review was conducted for studies where results of tests for contaminants in drinking water were disseminated to populations whose water supply posed a known health risk. Studies of any design were included where data were available from a contemporaneous comparison or control group. Using multiple sources >14,000 documents were located. Six studies met inclusion criteria (four of arsenic contamination and two of microbiological contamination). Meta-analysis was not possible in most cases due to heterogeneity of outcomes and study designs. Outcomes included water quality, change of water source, treatment of water, knowledge of contamination, and urinary arsenic. Source switching was most frequently reported: of 5 reporting studies 4 report significantly higher rates of switching (26–72%) among those who received a positive test result and a pooled risk difference was calculate for 2 studies (RD = 0.43 [CI0.4.0–0.46] 6–12 months post intervention) suggesting 43% more of those with unsafe wells switched source compared to those with safe wells. Strength of evidence is low since the comparison is between non-equivalent groups. Two studies concerning fecal contamination reported non-significant increases in point-of-use water treatment. Conclusion Despite the publication of some large cohort studies and some encouraging results the evidence base to support dissemination of contamination data to improve water management is currently equivocal. Rigorous studies on this topic are needed, ideally using common outcome measures.
On Scalable Attack Detection in the Network

Current intrusion detection and prevention systems seek to detect a wide class of network intrusions (e.g., DoS attacks, worms, port scans) at network vantage points. Unfortunately, even today, many IDS systems we know of keep per-connection or per-flow state to detect malicious TCP flows. Thus, it is hardly surprising that these IDS systems have not scaled to multi-gigabit speeds. By contrast, both router lookups and fair queuing have scaled to high speeds using aggregation via prefix lookups or DiffServ. Thus, in this paper, we initiate research into the question as to whether one can detect attacks without keeping per-flow state. We will show that such aggregation, while making fast implementations possible, immediately causes two problems. First, aggregation can cause behavioral aliasing where, for example, good behaviors can aggregate to look like bad behaviors. Second, aggregated schemes are susceptible to spoofing by which the intruder sends attacks that have appropriate aggregate behavior. We examine a wide variety of DoS and scanning attacks and show that several categories (bandwidth based, claim-and-hold, port-scanning) can be scalably detected. In addition to existing approaches for scalable attack detection, we propose a novel data structure called partial completion filters (PCFs) that can detect claim-and-hold attacks scalably in the network. We analyze PCFs both analytically and using experiments on real network traces to demonstrate how we can tune PCFs to achieve extremely low false positive and false negative probabilities
Multiaspect Classification of Sidescan Sonar Images: Four Different Approaches to Fusing Single-Aspect Information

In this paper, the classification of an object on the seabed from two sidescan sonar looks is considered. Four different approaches to fusing the information from the individual looks are described. The first method uses a kernel regression classification method with the combined feature (CF) vectors from the two looks. The other three approaches are based upon the Dempster-Shafer (DS) fusion of the outputs from a single-look kernel-based classifier. They differ with respect to the manner in which the DS masses for each look are derived from the single-look classifier. The four approaches are evaluated with Klein 5500 sidescan sonar data collected from four classes: rock and three dummy mine types: manta, rockan, and cylinder. The sonar data were collected in October 2005 when the Defence Research and Development Canada Atlantic (DRDC-Atlantic, Dartmouth, NS, Canada), participated with the NATO Undersea Research Centre (NURC, La Spezia, Italy) and Groupe D'Études Sous-Marines de l'Atlantique (GESMA, Brest, France) in a joint trial (CITADEL) with the DRDC remote, semisubmersible vehicle DORADO. Using these data, it is shown that two of the approaches for DS mass assignments yield two-look classification performances very similar to each other and to the CF method. The DS approaches have the advantage that they do not require explicit training with a CF set.
Expression of the ERBB2 protein in benign and malignant salivary gland tumors

Fifty‐two primary human salivary gland tumors were analyzed for expression of the p 185ERBB2 protein using immunohistochemical and immunoblotting techniques. About 63% (33/52) of the tumors expressed the ERBB2 protein. The highest expression levels were detected among the carcinomas, where 32% of the tumors showed intense membrane staining in 25–100% of the tumor cells. In benign pleomorphic adenomas, the corresponding figure was only 12%. Clinical follow‐up data available for 18 of the 19 patients with carcinomas suggested an association between high ERBB2 protein levels and poor prognosis as measured by recurrence of disease and/or the appearance of metastases. These results indicate that ERBB2 activation and overexpression could be an important genetic event with possible prognostic implications in a subset of malignant salivary gland tumors.
Compilation of the Balanced Corpus of Contemporary Written Japanese in the KOTONOHA Initiative (Invited Paper)

Compilation of a hundred million word balanced corpus named Balanced Corpus of Contemporary Written Japanese (BCCWJ) is underway at the National Institute for Japanese Language. This corpus is a component of the KOTONOHA super-corpus that covers the full range of modern Japanese from the middle of the 19th century up to the present. The unique characteristics of the BCCWJ consists in that about two third of the samples in the corpus were randomly selected from two statistical populations: one of them consists in the publication data of books, magazines, and newspapers during the years 2001-2005, and the other consists of the set of books registered in more than 13 public libraries of Tokyo metropolis (335,000 different books). The corpus will be publicly available in the first half of 2011.
Development and Evaluation of SoySNP50K, a High-Density Genotyping Array for Soybean

The objective of this research was to identify single nucleotide polymorphisms (SNPs) and to develop an Illumina Infinium BeadChip that contained over 50,000 SNPs from soybean (Glycine max L. Merr.). A total of 498,921,777 reads 35–45bp in length were obtained from DNA sequence analysis of reduced representation libraries from several soybean accessions which included six cultivated and two wild soybean (G. soja Sieb. et Zucc.) genotypes. These reads were mapped to the soybean whole genome sequence and 209,903 SNPs were identified. After applying several filters, a total of 146,161 of the 209,903 SNPs were determined to be ideal candidates for Illumina Infinium II BeadChip design. To equalize the distance between selected SNPs, increase assay success rate, and minimize the number of SNPs with low minor allele frequency, an iteration algorithm based on a selection index was developed and used to select 60,800 SNPs for Infinium BeadChip design. Of the 60,800 SNPs, 50,701 were targeted to euchromatic regions and 10,000 to heterochromatic regions of the 20 soybean chromosomes. In addition, 99 SNPs were targeted to unanchored sequence scaffolds. Of the 60,800 SNPs, a total of 52,041 passed Illumina’s manufacturing phase to produce the SoySNP50K iSelect BeadChip. Validation of the SoySNP50K chip with 96 landrace genotypes, 96 elite cultivars and 96 wild soybean accessions showed that 47,337 SNPs were polymorphic and generated successful SNP allele calls. In addition, 40,841 of the 47,337 SNPs (86%) had minor allele frequencies ≥10% among the landraces, elite cultivars and the wild soybean accessions. A total of 620 and 42 candidate regions which may be associated with domestication and recent selection were identified, respectively. The SoySNP50K iSelect SNP beadchip will be a powerful tool for characterizing soybean genetic diversity and linkage disequilibrium, and for constructing high resolution linkage maps to improve the soybean whole genome sequence assembly.
De Jong's Sphere Model Test for A Social-Based Genetic Algorithm (SBGA)

,Summary In this paper, we used the De Jong’s first function 1, “The Sphere Model” to compare values and results concerning the averages and best fits of both, the Simple Standard Genetic Algorithm (SGA), and a new approach of Genetic Algorithms named Social-Based Genetic Algorithm (SBGA). Results from the Sphere Model test on Social-Based Genetic Algorithms (SBGA) are obtained. These results are encouraging in that the Social-Based Genetic Algorithms (SBGA) performs better in finding best fit solutions of generations in different populations than the Simple Standard Genetic Algorithm.
Phase-field modeling for ferroelectrics in a multi-scale approach

Today’s development and improvement of ferroelectric materials is mainly based on experimental approaches. In order to significantly reduce development time and costs in the future, there is a demand for a virtual material development. The primary objective of this thesis is applying phase-field modeling in a knowledge based multi-scale simulation approach for the ferroelectric polycrystalline ceramics lead titanate (PTO) and lead zirconate titanate (PZT). Within this approach, phase-field modeling bridges the gap between predictive atomistic methods on one side and micromechanical modeling methods on the other side. Therefore, two interfaces in this multi-scale simulation chain have been developed and established in this work. In order to link the atomic level to the meso-scale, results from first-principles calculations and atomistic shell-model simulations are employed as input parameters for the phase-field model. The core of a phase-field model is its thermodynamical free energy function, containing all crystallographic and domain wall information of the ferroelectric material. Based on a sensitivity analysis of the coefficients of the free energy function, a novel adjustment method has been developed for these coefficients that solely requires input parameters from atomistic calculations and thereby is completely knowledge based. Furthermore, the free energy function of the phase-field model has been improved by introducing a new elastic energy term: It allows for a separate adjustment of the cubic and tetragonal elastic properties for PTO and PZT, as well as an independent fitting of the spontaneous strains and the piezoelectric coefficients. Typical ferroelectric domain configurations have been identified and investigated under electromechanical loading. The obtained domain effective small-signal and large-signal parameters serve as input for micromechanical modeling methods, thereby bridging the gap between the mesoand the micro-scale in the simulation chain. Therefore, the adjusted phase-field model has been implemented into a finite-element formulation. By investigating the monodomain state, the 90◦ domain stack as well as multidomain configurations, and taking defect mechanisms such as electrically charged point defects and grain boundaries into account, reversible domain wall motion and bending have been identified as governing processes on the meso-scale influencing the small-signal behavior. Furthermore, a clear correlation between the complexity of a domain structure and the resulting coercive field strength for initiating irreversible switching processes has been illustrated by the performed large-signal analysis.