Miracle-dz/UniFAR-FTUs huggingface dataset:
Group Size and Measures of Group-Level Properties: An Examination of Eta-Squared and ICC Values

The eta-squared (η2) from a one-way random effects ANOVA is an index commonly used to estimate group-level properties of data in multilevel research. Under some circumstances, however, η2 values provide biased estimates of the group-level properties. Biased estimates occur because the magnitude of the 1.12 in a one-way rando m effects ANOVA is partially a function of group size. In this paper, the relationship between group size and η is described, and a simulation verifying the relationship between group size and 112 is conducted. The simulation demonstrates the conditions under which η does and does not provide a biased estimate of group-level properties. The paper concludes by (a) discussing corrections for η2, and (b) providing guidelines for calculating estimates of group-level properties in samples having unequal group sizes.
Calibration based on duration quality measure function in noise robust speaker recognition for N IST SRE'12

This paper presents the performance evaluation of i-vector and PLDA based speaker recognition system which incorporate quality measures function (QMF) in linear calibration. Evaluated on the recent NIST SRE’12 corpus, the linear calibration with QMF as the additional term shows a positive gain in the system performance compared to the conventional linear calibration with only two terms. Based on the equal error rate values measured from our I4U evaluation trial set, the QMF calibration approach shows 10 – 37 % relative improvement compared to the conventional linear calibration. It is shown that by adding 1 – 2 extra parameters in the linear calibration through QMF approach, there is a potential to improve the calibration and discrimination performances of a speaker recognition system.
Design Patterns and General Video Game Level Generation

Design patterns have become a vital solution for a number of problems in software engineering. In this paper, we have performed rhythmic analysis of General Video Game Level Generation (GVG-LG) framework and have discerned 23 common design patterns. In addition, we have segregated the identified patterns into four unique classes. The categorization is based on the usage of identified patterns in game levels. Our future aim is to employ these patterns as an input for a search based level generator.
Measuring Geographic Concentration by Means of the Standard Deviational Ellipse

Many social problems involve the geographic location of the social factors concerned. To know the characteristics of the areas in which these factors appear is to throw light on the entire situation. A statistical method for measuring the concentration of unit locations on a "spot map" is indicated. The symbolism has been kept parallel, as far as possible, to that used in the statistics of frequency distributions.
Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data

Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from microarray gene expression profiling data. We overview each of strategies and introduce representative methods respectively. Their assumptions, advantages, shortcomings, and possible improvements and extensions are also clarified and commented.
Group I Metabotropic Glutamate Receptors Control Metaplasticity of Spinal Cord Learning through a Protein Kinase C-Dependent Mechanism

Neurons within the spinal cord can support several forms of plasticity, including response–outcome (instrumental) learning. After a complete spinal transection, experimental subjects are capable of learning to hold the hindlimb in a flexed position (response) if shock (outcome) is delivered to the tibialis anterior muscle when the limb is extended. This response-contingent shock produces a robust learning that is mediated by ionotropic glutamate receptors (iGluRs). Exposure to nociceptive stimuli that are independent of limb position (e.g., uncontrollable shock; peripheral inflammation) produces a long-term (>24 h) inhibition of spinal learning. This inhibition of plasticity in spinal learning is itself a form of plasticity that requires iGluR activation and protein synthesis. Plasticity of plasticity (metaplasticity) in the CNS has been linked to group I metabotropic glutamate receptors (subtypes mGluR1 and mGluR5) and activation of protein kinase C (PKC). The present study explores the role of mGluRs and PKC in the metaplastic inhibition of spinal cord learning using a combination of behavioral, pharmacological, and biochemical techniques. Activation of group I mGluRs was found to be both necessary and sufficient for metaplastic inhibition of spinal learning. PKC was activated by stimuli that inhibit spinal learning, and inhibiting PKC activity restored the capacity for spinal learning. Finally, a PKC inhibitor blocked the metaplastic inhibition of spinal learning produced by a group I mGluR agonist. The data strongly suggest that group I mGluRs control metaplasticity of spinal learning through a PKC-dependent mechanism, providing a potential therapeutic target for promoting use-dependent plasticity after spinal cord injury.
Medicinal Plants Used by a Mbyá-Guarani Tribe against Infections: Activity on KPC-Producing Isolates and Biofilm-Forming Bacteria

The traditional use of medicinal plants for treatment of infectious diseases by an indigenous Mbyá-Guarani tribe from South Brazil was assessed by evaluating the antibiotic and antibiofilm activities against relevant bacterial pathogens. Aqueous extracts from 10 medicinal plants were prepared according to indigenous Mbyá-Guarani traditional uses. To evaluate antibiotic (OD600) and antibiofilm (crystal violet method) activities, Pseudomonas aeruginosa ATCC 27853, Staphylococcus epidermidis ATCC 35984 and seven multi-drug resistant Klebsiella pneumoniae carbapenemase (KPC)-producing bacterial clinical isolates were challenged with the extracts. Furthermore, the susceptibility profile of KPC-producing bacteria and the ability of these isolates to form biofilm were evaluated. The plants Campomanesia xanthocarpa, Maytenus ilicifolia, Bidens pilosa and Verbena sp. showed the best activity against bacterial growth and biofilm formation. The majority of KPC-producing isolates, which showed strong ability to form biofilm and a multidrug resistance profile, was inhibited by more than 50% by some extracts. The Enterobacter cloacae (KPC 05) clinical isolate was the only one resistant to all extracts. This study confirms the importance of indigenous traditional medicinal knowledge and describes for the first time the ability of these plants to inhibit biofilm formation and/or bacterial growth of multi-drug resistant KPC-producing isolates.
Finite-Horizon ${\mathcal H}_{\infty }$ Consensus Control of Time-Varying Multiagent Systems With Stochastic Communication Protocol

This paper is concerned with the distributed <inline-formula> <tex-math notation="LaTeX">${\mathcal {H}}_{\infty }$ </tex-math></inline-formula> consensus control problem for a discrete time-varying multiagent system with the stochastic communication protocol (SCP). A directed graph is used to characterize the communication topology of the multiagent network. The data transmission between each agent and the neighboring ones is implemented via a constrained communication channel where only one neighboring agent is allowed to transmit data at each time instant. The SCP is applied to schedule the signal transmission of the multiagent system. A sequence of random variables is utilized to capture the scheduling behavior of the SCP. By using the <italic>mapping technology</italic> combined with the <italic>Hadamard product</italic>, the closed-loop multiagent system is modeled as a time-varying system with a <italic>stochastic parameter matrix</italic>. The purpose of the addressed problem is to design a cooperative controller for each agent such that, for all probabilistic scheduling behaviors, the <inline-formula> <tex-math notation="LaTeX">${\mathcal {H}}_{\infty }$ </tex-math></inline-formula> consensus performance is achieved over a given finite horizon for the closed-loop multiagent system. A necessary and sufficient condition is derived to ensure the <inline-formula> <tex-math notation="LaTeX">$ {\mathcal {H}}_{ \infty }$ </tex-math></inline-formula> consensus performance based on the completing squares approach and the stochastic analysis technique. Then, the controller parameters are obtained by solving two coupled backward recursive Riccati difference equations. Finally, a numerical example is given to illustrate the effectiveness of the proposed controller design scheme.
Z-Set and Independent Fault Set based Fault Pair Collapsing for Fault List Reduction

Chinju.G, J.P.Anita Abstract— In fault pair collapsing, certain fault pairs are eliminated from the fault list, since those fault pairs are guaranteed to be distinguished by the remaining fault pairs in the fault list. Considering a fault pair is important in the case of diagnostic fault simulation and test generation. The concept of Z-set and independent fault set are used for fault pair formation. Z-set characteristics determine the numbers of fault pairs that are guaranteed to be distinguished by a given fault detection test set. So the remaining fault pairs are considered for further fault pair collapsing process. Independent fault pairs are formed from the collapsed fault list such that each fault in that pair cannot be covered by the tests derived for another fault. For fault pair collapsing process, a fault pair is selected which is not included in the independent fault set. Hence a reduction in the number of fault pairs is obtained. Again to further reduce the numbers of fault pairs, dominance relations between the faults are considered. Index Terms—Diagnostic test generation, Distinguishable fault pairs, Dominance and Equivalence in fault pairs, Fault pair collapsing, Fault Pair forming, Independent fault set, Z-set.
HepG2 Cells Expressing MicroRNA miR-122 Support the Entire Hepatitis C Virus Life Cycle

ABSTRACT The liver-specific microRNA miR-122 is required for efficient hepatitis C virus (HCV) RNA replication both in cell culture and in vivo. In addition, nonhepatic cells have been rendered more efficient at supporting this stage of the HCV life cycle by miR-122 expression. This study investigated how miR-122 influences HCV replication in the miR-122-deficient HepG2 cell line. Expression of this microRNA in HepG2 cells permitted efficient HCV RNA replication and infectious virion production. When a missing HCV receptor is also expressed, these cells efficiently support viral entry and thus the entire HCV life cycle.
Determination of salidroside and tyrosol in Rhodiola by capillary electrophoresis with graphene/poly(urea‐formaldehyde) composite modified electrode

This report describes the fabrication and application of a novel graphene/poly(urea‐formaldehyde) composite modified electrode as a sensitive amperometric detector of CE. The composite electrode was fabricated on the basis of the in situ polycondensation of a mixture of graphenes and urea–formaldehyde prepolymers on the surface of a platinum disc electrode. It was coupled with CE for the separation and detection of salidroside and tyrosol in Rhodiola, a traditional Chinese medicine, to demonstrate its feasibility and performance. Salidroside and tyrosol have been well separated within 6 min in a 40 cm long capillary at a separation voltage of 12 kV using a 50 mM borate buffer (pH 9.8). The prepared graphene‐based CE detector offered significantly lower detection potential, yielded enhanced signal‐to‐noise characteristics, and exhibited high resistance to surface fouling and enhanced stability. It showed long‐term stability and reproducibility with relative standard deviations of less than 5% for the peak current (n=15).
A Latent Topic Based Collaborative Filtering Recommendation Algorithm for Web Communities

Providing personalized high quality community recommendation for Web community members has become increasingly important. Traditional collaborative filtering methods based on explicit topic associations cannot solve the information sparsity problem. The recommendation methods based on latent topic association results in inaccurate results. To solve the above problems, we propose a collaborative Web community recommendation algorithm based on latent topic. Our algorithm generates the latent link between communities and members using latent topic associations to overcome the sparsity problem. Our algorithm also reduces inaccurate results by combining similar members' behaviors and interests. The experiment indicates that our recommendation algorithm has higher recommendation accuracy than traditional methods.
Image Segmentation and Feature Extraction

An overview of present computer techniques of partitioning continuous-tone images into meaningful segments and of characterizing these segments by sets of "features" is presented. Segmentation often consists of two methods:boundary detection and texture analysis. Both of these are discussed. The design of the segmenter and feature extractor are intimately related to the design of the rest of the image analysis system¿particularly the preprocessor and the classifier. Toward aiding this design, a few guidelines and illustrative examples are included.
Cultural and social disconnection in the context of a changed physical environment

Abstract. The context of the study was provided by the enforced relocation of an old coal mining community in the UK and describes the changes that were experienced by relocatees. The study is longitudinal in design over a six year period and this article is based on the qualitative part of the study. The old village had consisted of five straight rows of terraced houses whereas the new village was built in a curvilinear design with additional housing, occupying a much larger space. Reduced visual access to others not only diminished a sense of connectedness but also restricted an information flow which had been part of the functioning of the previous community, leaving indigenous participants with a sense of isolation. This unwanted isolation diluted the previous collective identity and weakened social support. In addition, an abrupt change in the community's socio‐cultural patterns occurred and previously learned privacy mechanisms were found to be inappropriate in the new setting. New values, priorities, lifestyles and overt materialism were evident and the data suggest that the earlier mostly collective functioning of the community had been replaced by individual functioning. It is proposed that spatial aspects provide constraints and opportunities for different behaviour patterns, highlighting the crucial importance of the physical environment and illustrating the essentially dynamic relationship between person, group and place.
Bidding Protocols for Deploying Mobile Sensors

Constructing a sensor network with a mix of mobile and static sensors can achieve a balance between sensor coverage and sensor cost. In this paper, we design two bidding protocols to guide the movement of mobile sensors in such sensor networks to increase the coverage to a desirable level. In the protocols, static sensors detect coverage holes locally by using Voronoi diagrams and bid mobile sensors to move. Mobile sensors accept the highest bids and heal the largest holes. Simulation results show that our protocols achieve suitable trade-off between coverage and sensor cost
Monocular rear approach indicator for motorcycles

Conventional rear-view mirrors on motorcycles only allow a limited visibility as they are shaky and cover a small field of view. Especially at high speeds with strong headwind, it is difficult for the rider to turn his head to observe blind spots. To support the rider in observing the rear and blind-spots, a monocular system that indicates approaching vehicles is proposed in this paper. The vision based indication relies on sparse optical flow estimation. In a first step, a rough separation of background and approaching object pixel motion is done in an efficient and computationally cheap way. In a post-processing step, pixel motion information is further checked on geometric meaningful transformations and continuity over time. As a prototype, the system has been mounted on a Honda Pan-European motorcycle plus monitor in the dashboard that shows the rear-view image to the rider. If an approaching object is detected, the rider gets an indication on the monitor. The rear-view on the monitor not only acts as HMI (Human Machine Interface) for the indication, but also significantly extends the visibility compared to mirrors. The algorithm has been extensively evaluated for relative speeds from 20 km/h to 100 km/h (speed differences between motorcycle and approaching vehicle), at normal, rainy and night conditions. Results show that the approach offers a sensing range from 20 m at low speed up to 60 m at night.
ECO Timing Optimization Using Spare Cells and Technology Remapping

We introduce in this paper a new problem of post-mask engineering change order (ECO) timing optimization using spare-cell rewiring and present a two-phase framework for this problem. Spare-cell rewiring is a popular technique for incremental timing optimization and/or functional change after the placement stage. The spare-cell rewiring problem is very challenging because of its dynamic wiring cost nature for selecting a spare cell, while the existing related problems consider only static wiring cost: once a standard cell is placed, its physical location is fixed and so is its wiring cost. For the spare-cell rewiring problem, each rewiring could make some spare cells become ordinary standard cells and some standard cells become new spare cells simultaneously. As a result, the wiring cost becomes dynamic and further complicates the optimization process. For the addressed problem, we present a two-phase framework of 1) buffer insertion and gate sizing followed by 2) technology remapping. For Phase 1, we present a dynamic programming algorithm considering the dynamic cost, called dynamic cost programming, for the ECO timing optimization with spare cells. Without loss of solution optimality, we further present an effective pruning method by selecting spare cells only inside an essential bounding polygon to reduce the solution space. For those ECO timing paths that cannot be fixed during Phase 1, we apply technology remapping on the spare cells to restructure the circuit to fix the timing violations. The whole framework is integrated into a commercial design flow. Experimental results based on five industry benchmarks show that our method is very effective and efficient in fixing the timing violations of ECO paths.
Determination of the illicit drug gamma‐hydroxybutyrate (GHB) in human saliva and beverages by 1H NMR analysis

High resolution 1H NMR spectroscopy has been employed to investigate the detection and quantification of the illicit ‘date‐rape’ drug gamma‐hydroxybutyrate (GHB) in both human saliva and a commonly‐consumed low‐alcohol beer product. Data acquired revealed that this multicomponent analytical technique provided unequivocal evidence for the detection of this agent by this technique in both of these matrices, i.e., all three of its resonances [those ascribable to the α‐CH2 (t, δ=2.25 ppm), β‐CH2 (tt, δ=1.81 ppm) and γ‐CH2 (t, δ=3.61 ppm) group protons] were present in spectra acquired on human saliva, and two of these (the α‐ and β‐CH2 group signals) in the beverage product examined, the latter observation attributable to overlap of the γ‐CH2 1H resonance with those of carbohydrates. Since good linear calibration relationships between the intensities of each of the NMR‐visible signals and added GHB concentration (the former normalised to that of an external 3‐trimethylsilyl [2,2,3,3‐2H4]‐ propionate standard present in a coaxial NMR tube insert) were observed, this illicit drug is also readily quantifiable in such multicomponent samples. Our data demonstrate the advantages offered by this technique when applied to the analysis of illicit drugs in multicomponent sample matrices such as human biofluids and beverage products.
Summarisation and novelty in Mobile Information Access

The paper presents a user study which investigates the effects of incorporating novelty detection in automatic text summarisation. The motivation being the need to provide access to information that is tailored to small screen displays. Automatic text summarisation offers a means to deliver device-friendly content. An effective summary could be one that includes only new information. However, a consequence of focusing exclusively on novel parts may result in a loss of context, which may have an impact on the ability to correctly interpret the meaning of a summary given the source document. In the user study we compares two strategies to produce summaries that incorporate novelty in different ways; an incremental summary and a constant length summary. The aim is to establish whether a summary that contains only novel sentences provides sufficient basis to determine relevance of a document, or do we need to include additional sentences to provide context. Findings from the study seem to suggest that there is minimal difference in performance for the tasks we set our users. Therefore, for the case of mobile information access a summary that contains only novel information would be more appropriate.
The Science Behind Curriculum Development and Evaluation

The production of an effective mathematics curriculum begins with a scientific development, evaluation, and revision framework. The purpose of this study was to conduct an initial investigation of a recently developed Tier 2 mathematics curriculum designed to improve the outcomes of first grade students at risk for mathematics difficulties (MD). The curriculum, which is anchored to a scientific design framework and a well-specified theory of change, centers on the careful integration of foundational concepts of whole number and validated-design principles of explicit and systematic instruction. Four instructional groups, with each consisting of five first grade students with MD and one interventionist, participated in the study. Data related to the feasibility, usability, and promise of the curriculum to improve student mathematics achievement were collected using multiple methods. Results provide preliminary evidence in terms of these curriculum development and evaluation areas. Implications for instruction and design research are discussed.