Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of two additives, locust bean gum (E-410) and guar gum (E-412), in food products by DNA-based methods

Locust bean gum (E-410) and guar gum (E-412) are high molecular weight galactomannans used by the food industry as versatile food additives. The compounds, although chemically closely related, do not have the same functional properties when used in foods, and the substitution or unadvertised addition of either could change the desired qualities of the product. Analytical discrimination between E-410 and E-412 is technically difficult since they only differ in their galactose: mannose ratios, being 1 : 4 and 1 : 2 for locust bean gum and guar gum, respectively. A qualitative DNA-based method is reported for the authentication of additives E-410 and E-412 in finished food products (ice cream, dehydrated desserts, milk derivatives, dehydrated soups, salad dressing, marmalade and meat) from small quantities of food. DNA sequences from the nuclear ribosomal spacers of Ceratonia siliqua and Cyamopsis tetragonoloba, the plant sources of E-410 and E-412, respectively, were used to design polymerase chain reaction primers specific for each additive (PA23/PA21 and PG22/PG21). Twenty-two foods were analysed for the presence of E-410 and E-412 additives by this single-step polymerase chain reaction-based method. Positive DNA amplifications with the E-410 and/or E-412 primers were obtained in all 19 samples reported to contain either additive.
Social categorization and similarity in intergroup behaviour

The present study is one of a series exploring the role of social categorization in intergroup behaviour. It has been found in our previous studies that in ‚minimal' situations, in which the subjects were categorized into groups on the basis of visual judgments they had made or of their esthetic preferences, they clearly discriminated against members of an outgroup although this gave them no personal advantage. However, in these previous studies division into groups was still made on the basis of certain criteria of ‚real' similarity between subjects who were assigned to the same category. Therefore, the present study established social categories on an explicitly random basis without any reference to any such real similarity. It was found that, as soon as the notion of ‚group' was introduced into the situation, the subjects still discriminated against those assigned to another random category. This discrimination was considerably more marked than the one based on a division of subjects in terms of interindividual similarities in which the notion of ‚group' was never explicitly introduced. In addition, it was found that fairness was also a determinant of the subjects' decisions. The results are discussed from the point of view of their relevance to a social-cognitive theory of intergroup behaviour.
MALDI Imaging‐Guided Microproteomic Analyses of Heterogeneous Breast Tumors—A Pilot Study

Matrix‐assisted laser desorption/ionization (MALDI) imaging is an ideal tool to study intratumor heterogeneity (ITH) and its implication in prognostic stratification of patients. However, there are some drawbacks concerning protein identification. On the other hand, laser microdissection (LMD)‐based microproteomics allows retrieving thousands of protein identifications from small tissue pieces. As a proof of concept, the authors combine these two complementary approaches to analyze heterogeneous regions in breast tumors. Invasive ductal breast cancer FFPE tissue sections from five patients are analyzed by MALDI imaging and the dataset is processed by segmentation. Heterogeneous regions within tumors are processed by LMD‐based microproteomics, in duplicates. Liquid chromatography‐tandem mass spectrometry data are classified by hierarchical clustering. Heterogeneous tissue regions are discriminated on the basis of their actual molecular heterogeneity. The dataset is correlated with MALDI imaging to identify m/z values discriminating heterogeneous regions. The molecular characterization of cell clones in tumors related to bad patient outcome could have great impact for pathology. A combined application of LMD‐based microproteomics and MALDI imaging for ITH studies is presented.
Pattern Prediction and Passive Bandwidth Management for Hand-over Optimization in QoS Cellular Networks with Vehicular Mobility

In wireless networking, the main desire of end-users is to take advantage of satisfactory services, in terms of QoS, especially when they pay for a required need. Many efforts have been made to investigate how the continuity of services can be guaranteed in QoS networks, where users can move from one cell to another one. The introduction of a prediction scheme with passive reservations is the only way to face this issue; however, the deployment of in-advance bandwidth leads the system to waste resources. This work consists of two main integrated contributions: a new pattern prediction scheme based on a distributed set of Markov chains, in order to handle passive reservations, and a statistical bandwidth management algorithm for the reduction of bandwidth wastage. The result of the integration is the Distributed Prediction with Bandwidth Management Algorithm (DPBMA) that is independent from the considered technology and the vehicular environment. Several simulation campaigns were conducted in order to evaluate the effectiveness of the proposed idea. It was also compared with other prediction schemes, in terms of system utilization, accuracy, call dropping, and call blocking probabilities.
A tutorial on onset detection in music signals

Note onset detection and localization is useful in a number of analysis and indexing techniques for musical signals. The usual way to detect onsets is to look for "transient" regions in the signal, a notion that leads to many definitions: a sudden burst of energy, a change in the short-time spectrum of the signal or in the statistical properties, etc. The goal of this paper is to review, categorize, and compare some of the most commonly used techniques for onset detection, and to present possible enhancements. We discuss methods based on the use of explicitly predefined signal features: the signal's amplitude envelope, spectral magnitudes and phases, time-frequency representations; and methods based on probabilistic signal models: model-based change point detection, surprise signals, etc. Using a choice of test cases, we provide some guidelines for choosing the appropriate method for a given application.
Denial of service detection by support vector machines and radial-basis function neural network

Denial of service (DoS) problem is one of serious attacks in the Internet. The attackers attempt to exhaust the resource of the service provider in order to prevent legitimate users from using the system. Most of the detecting DoS tools, such as rule-based and threshold detection approaches, rely on the objective opinion of the domain experts. This work aims to apply machine learning techniques, such as radial-basis function neural network (RBFNN) and support vector machines (SVM), to solve the DoS problem and compare which technique, is better to detect DoS. The main advantage of this detection method is that it has the ability to detect or predict new attacks when some patterns are similar to the attack patterns learnt in the past. Thus it can detect novel attacks for which signatures have not been defined.
Clearance of apoptotic neurons without inflammation by microglial triggering receptor expressed on myeloid cells-2

Elimination of apoptotic neurons without inflammation is crucial for brain tissue homeostasis, but the molecular mechanism has not been firmly established. Triggering receptor expressed on myeloid cells-2 (TREM2) is a recently identified innate immune receptor. Here, we show expression of TREM2 in microglia. TREM2 stimulation induced DAP12 phosphorylation, extracellular signal–regulated kinase phosphorylation, and cytoskeleton reorganization and increased phagocytosis. Knockdown of TREM2 in microglia inhibited phagocytosis of apoptotic neurons and increased gene transcription of tumor necrosis factor α and nitric oxide synthase-2, whereas overexpression of TREM2 increased phagocytosis and decreased microglial proinflammatory responses. Thus, TREM2 deficiency results in impaired clearance of apoptotic neurons and inflammation that might be responsible for the brain degeneration observed in patients with polycystic lipomembranous osteodysplasia with sclerosing leukoencephalopathy/Nasu-Hakola disease.
Applying Generalizability Theory for Making Quantitative RTI Progress-Monitoring Decisions

Language in the Individuals With Disabilities Education Improvement Act (IDEIA) allows the use of response-to-intervention (RTI) methodology in the identification of specific learning disabilities. However, there is no consensus on decision rules using curriculum-based measurement of oral reading fluency (CBM-R) for defining responsiveness. The purpose of this article is to describe how to apply generalizability (G) theory for making quantitative high-stakes RTI decisions. A sample of 68 first-grade students (36 females and 32 males) was randomly administered the first-grade Dynamic Indicators of Basic Early Literacy Skills oral reading fluency probes and correct words per minute (CWPM) were calculated for conducting both a generalizability (G) study and a decision (D) study using G theory. The results showed that the average raw scores (CWPM) across 20 probes encompassed a wide range from a low of 69 CWPM to a high of 88 CWPM. In addition, 90.2% of the variance was due to student reading skill, 7.0% was due to unaccounted sources of error, and only 2.8% was due to passage or probe variability. Also, the increasing number of probes administered (from 1 to 9) considerably reduced the values of standard error of measurement and increased the reliability coefficients. An example is provided to demonstrate how to apply G theory in using CBM-R data to guide psychometrically valid RTI decisions at the individual student level.
Enabling supplier discovery through a part-focused manufacturing process ontology

ABSTRACT Numerous ontologies have been introduced to represent and activate engineering knowledge across the development process. However, many of the ontologies in the manufacturing domain provide limited usability for individuals who lack knowledge of manufacturing processes available within the domain. Similarly, web-based e-sourcing portals lack the ability to adequately pair components whose developers have limited knowledge of manufacturing processes with manufacturers who are able to produce their product. Motivated by these current gaps, an ontology is proposed which is designed to enable both users with a limited knowledge and those with a pre-existing knowledge of manufacturing to identify potential processes. The Part-focused Manufacturing Process Ontology is designed around the concept that manufacturing processes can be selected based upon desired features and attributes of a component/product. This differs from other ontologies that model the manufacturing process domain on the characteristics of the resources utilised in manufacturing. Further, the ontology is populated with some manufacturer data and its functionality demonstrated using component cases.
Design of Digital IIR Low Pass Filter Using Particle Swarm Optimization ( PSO )

Digital filter plays an important role in today’s world of computation and communication. On the other hand to design a digital infinite impulse response (IIR) filter satisfying all the required conditions is a challenging one. This paper develops innovative methodology for the stable, efficient and robust design of digital IIR low pass(LP) filter using Particle Swarm Optimization (PSO) method. PSO is a random algorithm which provides optimal filter coefficients such that error function is minimized when compared with the traditional IIR filter design techniques. PSO offers many advantages like simplicity in implementation, robustness against local minima, ability to converge to a reasonably good solution. Our simulation study confirms that the purposed approach is accurate and has a fast convergence speed and the results obtained illustrates that PSO offers a viable tool to design IIR filters. KeywordsDigital IIR filter, gbest, Low-pass filter(LP), Particle Swarm Optimization, pbest, weighting factors.
Semantic adaptation of consumer photo for mobile device access

This paper proposes a novel event-aware semantic image adaptation framework for accessing consumer photos via mobile devices. There are two major challenges to develop such an image adaptation framework: (1) how to bridge the semantic gap in the search for the desired photos from a consumer database; (2) how to perform appropriate adaptation for various small displays in order to maximize user's perceptual experience according to the semantic significance of objects in photos. To meet the first challenge, an event semantics-guided extraction is developed based on statistical fusion of bottom-up low level features and top-down semantic features. To meet the second challenge, a key object-based semantic adaptation approach is designed to obtain the perceptually optimized Region of Interest (ROI). We conducted experiments based on the events defined in the Kodak consumer photo database [2]. These experiments show that by utilizing the semantics of the photos with event-based a priori knowledge, the adaptation result outperforms the conventional attention based scheme. More importantly, the proposed framework can be easily extended to other events by adopting the event semantics based a priori knowledge into the adaptation system.
Inhibition of PCR in Genital and Urine Specimens Submitted for Chlamydia trachomatis Testing

ABSTRACT We determined the frequency of PCR inhibition in genital and urine specimens submitted for Chlamydia trachomatis testing using the internal control DNA provided with the COBAS AMPLICOR C. trachomatis test and assessed methods to remove it. Inhibition occurred in 65 of 906 (7%) cervical swabs, 23 of 51 (45%) urethral swabs, and 2 of 175 (1.1%) urine samples. Overall, inhibition was eliminated in processed specimens after storage at 4°C in 77 of 90 specimens (86%), freezing at −70°C in 59 of 82 specimens (72%), storage at 4°C followed by either 1:100 dilution in 37 of 43 specimens (86%) or 1:10 dilution in 42 of 47 specimens (89%), and phenol-chloroform extraction in 79 of 80 specimens (99%). No positive specimens were missed due to inhibition. We conclude that PCR inhibition is rare with urine specimens and infrequent with endocervical swabs but occurs frequently with urethral swabs. The frequency of PCR inhibition may be significantly reduced by methods which can be easily incorporated into the processing of specimens.
Confucianism and early childhood education: a study of young children's responses to traditional Chinese festival stories

The teaching of values has seen renewed interest, as educators, policymakers and parents seek ways of increasing peaceful coexistence for children in a conflict‐driven world. Education systems are again reviewing values as part of their core mission. Confucian values form the core of most Asian cultures, penetrating different levels of social life, and also set the standards for most families, communities and political behaviour. The research reported in this study set out to examine young children's expressed views of Confucian values represented in traditional stories of four Chinese festivals. Within this research, Confucian values were centred on five virtues: Ren (benevolence), Yi (righteousness), Li (courteousness), Xiao (filial piety), and Zhi (wisdom). The four selected Chinese festivals were: (1) Chinese New Year, (2) Dragon Boat festival, (3) Chung Yeung festival, and (4) Mid‐Autumn festival. Participants included 392 children aged four to five years from 29 kindergartens or nursery schools and 57 pre‐service early childhood teachers in Hong Kong. Results showed that the values of Ren (benevolence) and Yi (righteousness) were the most popular responses among local young children, while the value of Li (courteousness) tended to be the least popular category. Some implications for curriculum planning in early childhood education are discussed arising from the study findings.
A pair selection algorithm for robust RO-PUF against environmental variations and aging

Physically Unclonable Functions (PUFs) have emerged as a promising security primitive for low-cost authentication and cryptographic key generation. However, PUF stability with respect to temporal variations still limits its utility and widespread acceptance. Previous techniques in the literature have focused on improving PUF robustness against voltage and temperature variations, but the issues associated with aging have been largely neglected. In this paper, we propose a reliable pair selection algorithm (RePa) that can generate reliable keys from an RO-PUF under aging, voltage, and temperature variations. The RePa approach selects RO pairs with both initial frequency difference and aging rate/slope in mind. The aging slope is predicted by exploiting correlation that exists between frequency variation with respect to voltage and frequency variation with respect to aging. We evaluate RePa with simulations to show that it achieves significant improvement over the current state of the art in terms of reliability and cost. The proposed approach can achieve ~ 3.0x more robust key with only ~ 2.3x more ROs required than the conventional RO-PUF pair selection for the same key size.
The Intratextual Fundamentalism Scale: cross-cultural application, validity evidence, and relationship with religious orientation and the Big 5 factor markers1

This paper introduces a new five-item cross-cultural fundamentalism scale based on the principle of intratextuality. Free of belief content and concerns with militancy, each of the five items taps into a different facet of intratextuality that collectively assess the attitudes that fundamentalists maintain toward their sacred text—namely, a persuasion that it is divine in origin, inerrant, privileged above all other texts, authoritative, and unchanging as the embodiment of timeless truth. In this article, we present three studies concerned with the Intratextual Fundamentalism Scale (IFS). Study 1 introduces the development, confirmatory factor analysis, and convergent validity of the IFS based on a sample of 119 Christians in the US as well as examines its relationship to religious orientation. Study 2 replicates the findings of the first study with a sample of 220 Muslims from Pakistan. Study 3 again confirms the structure of the IFS, addresses divergent validity, and investigates its relationship with religious orientation and Goldberg's Big 5 factor markers in a sample of 227 US Christians. Findings of all three studies suggest that the IFS is a psychometrically sound instrument that economically assesses religious fundamentalism without religious content bias or concern for aggression. Results also indicate that, only for Americans, fundamentalism, as measured by the IFS, is significantly related to intrinsic (r = 0.35; r = 0.51) and extrinsic-personal (r = 0.33; r = 0.23) religious orientations, but not extrinsic-social orientation.
Sea surface wind speed inversion using low incident NRCS

As the launch of radars, such as the Precipitation Radar (PR) on Tropical Rainfall Measuring Mission (TRMM)[1] satellite and the Surface Wave Investigation and Monitoring (SWIM) on China France Oceanography SATellite (CFOSAT)[2], that operate in low incident angles, more and more NRCS data at low incident angle will be obtained. In order to retrieve the sea surface wind speed using low incident angle NRCS, the empirical GMF of NRCS with wind speed is established. The empirical nadir reflection coefficient |R(0)2| are calculated and the empirical relationship between mean square slop s(u) and wind speed is established. The mean square slop s(u) can be retrieved by fitting the NRCS at certain incident angles with the theoretical Gaussian GMF model. Then the wind speeds are calculated using the empirical corresponding relation between mean square slop and wind speed. The retrieved wind speeds are compared with Tao and NDBC buoy. The results show that the standard deviation (STD) and bias of retrieved wind speeds are smaller than 1.7m/s and 0.1m/s respectively.
Structural Features Extraction for Handwritten Arabic Personal Names Recognition

Due to the nature of handwriting with high degree of variability and imprecision, obtaining features that represent words is a difficult task. In this research, a features extraction method for handwritten Arabic word recognition is investigated. Its major goal is to maximize the recognition rate with the least amount of elements. This method incorporates many characteristics of handwritten characters based on structural information (loops, stems, legs, diacritics). Experiments are performed on Arabic personal names extracted from registers of the national Tunisian archive and on some Tunisian city names of IFN-ENIT database. The obtained results presented are encouraging and open other perspectives in the domain of the features and classifiers selection of Arabic Handwritten word recognition.
Adopting software product line principles to manage software variants in a complex avionics system

Eurocopter is the majority partner in NH Industries, the international consortium that develops and produces the medium weight multi-role helicopter NH90. AgustaWestland and Stork Fokker are additional partners. The NH90 has been successfully sold to 14 nations and their armed forces. The software division at Eurocopter Germany develops the on-board software for three computers of the NH90 avionics CORE and MISSION Systems. The growing number of customers and their specific application domains for the NH90 has led to an increasing number of functionally different helicopter variants. Moreover, during the long development time that is typical for complex military avionics projects, the computing technology has changed considerably over time so that the current operational software has to fit to several processor architectures. In order to cope with the high number of software variants and technology variations, the NH90 software team developed concepts and strategies for SW architecture and tool modifications based on Software Product Line (SPL) principles.
Fast Implementation of Lemke's Algorithm for Rigid Body Contact Simulation

We present a fast method for solving rigid body contact problems with friction, based on optimizations incorporated into Lemke’s algorithm for solving linear complementarity problems. These optimizations improve computation time in general and reduce the expected solution complexity from O(n3) to nearly O(nm + m3), where n and m are the number of contacts and rigid bodies. For a fixed number of bodies the expected complexity is therefore close to O(n) . Our method also improves numerical robustness, and removes the need to explicitly compute the large matrices associated with rigid body contact problems.