Miracle-dz/UniFAR-FTUs huggingface dataset:
Giant Magnetoresistance in a Single Thin Film of Permalloy

An experiment was constructed to measure giant magnetoresistance (GMR) in a 100-nm thick film of permalloy. After removing competing effects such as anisotropic magnetoresistance and eliminating all false positive signals, measurements indicate the presence of a domain wall but no definitive GMR signal. Alternative methods are in progress, which will hopefully resolve the difficulties with the initial measurement.
Effect of image quality, color, and format on the measurement of retinal vascular fractal dimension.

PURPOSE Fractal dimension of retinal vasculature is a global summary measure of retinal vascular network pattern and geometry. This study was conducted to examine the effect of variations in image color, brightness, focus, contrast, and format on the measurement of retinal vascular fractal dimension. METHODS A set of 30 retinal images from the Blue Mountains Eye Study was used for a series of experiments by varying brightness, focus (blur), contrast, and color (color versus monochrome). The original and the modified images were graded for fractal dimension (D(f)) using dedicated retinal imaging software (IRIS-Fractal). A further set of 20 grayscale images was used to compare image format (.jpg versus .tif) with regard to the resultant D(f) and processing time. RESULTS The mean D(f) of original images in this sample was 1.454. Compared with the original set of images, variations in brightness, focus, contrast, and color affected the measurements to a small to moderate degree (Pearson correlation coefficient, r, ranged from 0.47 to 0.97). Very dark or blurry images resulted in a substantially lower estimate of D(f). Monochrome images were also consistently associated with lower D(f) compared with that obtained from color images. Using . jpg or . tif image formats did not affect the measurement or the time needed to process and measure D(f). CONCLUSIONS Variations in image brightness, focus, and contrast can significantly affect the measurement of retinal vascular fractals. Standardization of image parameters and consistent use of either monochrome or color images would reduce measurement noise and enhance the comparability of the results.
An agent-based privacy-enhancing model

Purpose – The purpose of this paper is to discuss a privacy‐enhancing model, which is designed to help web users protect their private information. The model employs a collection of software agents. Privacy‐related decisions are made based on Platform for Privacy Preferences Project (P3P) information collected by the agents.Design/methodology/approach – Based on P3P information collected and user preferences, the software agents play a role in the decision‐making process. This paper presents the design of the agent‐based privacy‐enhancing model and considers the benefits and utility of such an approach.Findings – It is argued that the approach is feasible and it provides an effective solution to the usability limitations associated with P3P.Research limitations/implications – The paper focuses primarily on usability issues related to P3P. Consequently, some of the ancillary security‐related issues that arise are not covered in detail. Also the paper does not cover the development of an appropriate ontolog.
Automatic Weighting for the Combination of TDOA and Acoustic Features in Speaker Diarization for Meetings

In the task of speaker diarization for meetings it has been shown in previous work that it is useful to use the time delay of arrival (TDOA) between the different audio channels in the meeting room as an extra source of information in addition to the acoustic features. When combining feature streams, we use a weight to control the relative contributions of the streams. In the past, this weight was determined using development data and the same weight value was applied to all meetings. In this paper we present a method for automatically determining the weight. A metric derived from the Bayesian information criterion (BIC) computed for each feature stream estimates the weight for each meeting on the initial clustering iteration and adapts its value throughout the diarization process. By using this technique we achieve a more robust system and up to 18.2% relative improvement over the method of tuning the weight on development data.
Serum microRNA-21 as a Potential Biomarker for Response to Hypomethylating Agents in Myelodysplastic Syndromes

Identification of biomarkers that predict responses to hypomethylating agents (HMAs) will allow optimal strategies for epigenetic therapy in myelodysplastic syndromes (MDS) to be established. Serum miR-21 was quantitatively measured in 58 MDS patients treated with HMAs and 14 healthy controls. Serum miR-192 was an internal control, and diagnostic performance was evaluated according to receiver operating characteristics (ROCs). ROC analysis indicated that serum miR-21 levels differentiated responders from non-responders with an area under the curve of 0.648 (95% confidence, 0.49 to 0.72). The baseline level of serum miR-21 was significantly lower in the responder group than in the non-responder group (P = 0.041). The overall response rate (ORR) of the high miR-21 group was significantly lower than that of the low miR-21 group (41.2 vs. 73.2%, P = 0.021). Progression-free survival (PFS) was significantly inferior in the high group versus the low group (14.0 vs. 44.5 months, P = 0.001). Multivariate analyses revealed that the initial serum miR-21 level (P = 0.001) and circulating blasts (P = 0.007) were prognostic factors for PFS. Serum miR-21 level was significantly associated with ORR and PFS in MDS patients treated with HMAs. Although validation with a large prospective study is required, serum miR-21 is a potential biomarker of epigenetic therapy in MDS patients.
Functional Forms of Optimum Spoofing Attacks for Vector Parameter Estimation in Quantized Sensor Networks

Estimation of an unknown deterministic vector from quantized sensor data is considered in the presence of spoofing attacks, which alter the data presented to several sensors. Contrary to the previous work, a generalized attack model is employed which manipulates the data using transformations with arbitrary functional forms determined by some attack parameters whose values are unknown to the attacked system. For the first time, necessary and sufficient conditions are provided under which the transformations provide a guaranteed attack performance in terms of Cramer-Rao Bound (CRB) regardless of the processing the estimation system employs, thus defining a highly desirable attack. Interestingly, these conditions imply that, for any such attack when the attacked sensors can be perfectly identified by the estimation system, either the Fisher information matrix (FIM) for jointly estimating the desired and attack parameters is singular or that the attacked system is unable to improve the CRB for the desired vector parameter through this joint estimation even though the joint FIM is nonsingular. It is shown that it is always possible to construct such a highly desirable attack by properly employing a sufficiently large dimension attack vector parameter relative to the number of quantization levels employed, which was not observed previously. To illustrate the theory in a concrete way, we also provide some numerical results which corroborate that under the highly desirable attack, attacked data are not useful in reducing the CRB.
Inference of gene regulatory network based on module network model with gene functional classifications

We propose a novel method for an exhaustive inference of gene regulatory networks from genome-wide expression data and biological knowledge. Our method performs the inferences based on module network model. In the model a module is a set of genes with similar features, and a network represents regulatory relationships among the modules. Our method makes modules using gene functional classification together with expression data. We apply our method to inferences of the networks of yeast cell-cycle. Modules inferred by our method show consistency with experimentally-determined results on yeast cell-cycle, especially on G1 phase. Robust modules built by our method permit us to infer informative regulatory relationships.
Two-Tape Simulation of Multitape Turing Machines

It has long been known that increasing the number of tapes used by a Turing machine does not provide the ability to compute any new functions. On the other hand, the use of extra tapes does make it possible to speed up the computation of certain functions. It is known that a square factor is sometimes required for a one-tape machine to behave as a two-tape machine and that a square factor is always sufficient. The purpose of this paper is to show that, if a given function requires computation time <italic>T</italic> for a <italic>k</italic>-tape realization, then it requires at most computation time <italic>T</italic> log <italic>T</italic> for a two-tape realization. The proof of this fact is constructive; given any <italic>k</italic>-tape machine, it is shown how to design an equivalent two-tape machine that operates within the stated time bounds. In addition to being interesting in its own right, the trade-off relation between number of tapes and speed of computation can be used in a diagonalization argument to show that if <italic>T</italic>(<italic>n</italic>) and <italic>U</italic>(<italic>n</italic>) are two time functions such that inf <italic>T</italic>(<italic>n</italic>) log <italic>T</italic>(<italic>n</italic>) ÷ <italic>U</italic>(<italic>n</italic>) = 0 then there exists a function that can be computed within the time bound <italic>U</italic>(<italic>n</italic>) but not within the time bound <italic>T</italic>(<italic>n</italic>).
A Life Cycle for the Development of Autonomic Systems: The E-mobility Showcase

Component ensembles are a promising way of building self-aware autonomic adaptive systems. This approach has been promoted by the EU project ASCENS, which develops the core idea of ensembles by providing rigorous semantics as well as models and methods for the whole development life cycle of an ensemble-based system. These methods specifically address adaptation, self-awareness, self-optimization, and continuous system evolution. In this paper, we demonstrate the key concepts and benefits of the ASCENS approach in the context of intelligent navigation of electric vehicles (e-Mobility), which itself is one of the three key case studies of the project.
A secure data repository for semantic federation of product information

A large amount of today's product data is spread into office files and not efficiently searchable. With the integration of unstructured data from distinct sources, recent product information systems will evolve into federated product information systems. A repository is the heart of such systems, storing and managing extracted facts and information. This paper presents methods to enhance the system's utility by integrating additional quality metadata, covering the information's freshness, origin and quality. Covered security aspects are access permissions on source documents which have to be propagated to the repository, and privacy issues, arising if personal data like user recommendations are stored. This is a position paper.
MBV: a method to solve sample mislabeling and detect technical bias in large combined genotype and sequencing assay datasets

Motivation: Large genomic datasets combining genotype and sequence data, such as for expression quantitative trait loci (eQTL) detection, require perfect matching between both data types. Results: We described here MBV (Match BAM to VCF); a method to quickly solve sample mislabeling and detect cross‐sample contamination and PCR amplification bias. Availability and Implementation: MBV is implemented in C ++ as an independent component of the QTLtools software package, the binary and source codes are freely available at https://qtltools.github. io/qtltools/. Contact: olivier.delaneau@unige.ch or emmanouil.dermitzakis@unige.ch Supplementary information: Supplementary data are available at Bioinformatics online.
Application of educational data mining on analysis of students' online learning behavior

Based on the log data generated in the “Engineering Mechanics Experiment” Autonomous Learning Platform designed and developed by our institution, firstly the related data of students' landing behavior and resources explored behavior are collected and pretreated. And then the feature of the students' study behavior are analyzed, based on the analysis the factors that affect the students' log in and resources explore behavior are acquired by the decision tree algorithm. According to the analysis the education workers can adjust and optimize the teaching strategies, improve the teaching process and the curriculum development, and then to organize the teaching content and build teaching mode according to the student's study behavior.
Dietary Glycemic Index , Glycemic Load , and Digestible Carbohydrate Intake Are Not Associated with Risk of Type 2 Diabetes in Eight European Countries 1 – 3

The association of glycemic index (GI) and glycemic load (GL) with the risk of type 2 diabetes remains unclear. We investigated associations of dietary GI, GL, and digestible carbohydrate with incident type 2 diabetes. We performed a case-cohort study nested within theEuropeanProspective Investigation intoCancer andNutritionStudy, including a randomsubcohort (n=16,835) and incident type 2 diabetes cases (n = 12,403). The median follow-up time was 12 y. Baseline dietary intakes were assessed using countryspecific dietary questionnaires. Country-specific HRwere calculated and pooled using random effects meta-analysis. Dietary GI, GL, and digestible carbohydrate in the subcohort were (mean6 SD) 566 4, 1276 23, and 2266 36 g/d, respectively. After adjustment for confounders, GI and GLwere not associated with incident diabetes [HR highest vs. lowest quartile (HRQ4) for GI: 1.05 (95%CI = 0.96, 1.16); HRQ4 for GL: 1.07 (95% CI = 0.95, 1.20)]. Digestible carbohydrate intake was not associated with incident diabetes [HRQ4: 0.98 (95% CI = 0.86, 1.10)]. In additional analyses, we found that discrepancies in the GI value assignment to foods possibly explain differences in GI associationswith diabetes within the same study population. In conclusion, an expansion of the GI tables and systematic GI value assignment to foodsmay be needed to improve the validity of GI values derived in such studies, after which GI associations may need reevaluation. Our study shows that digestible carbohydrate intake is not associated with diabetes risk and suggests that diabetes risk with high-GI and -GL diets may be more modest than initial studies suggested. J. Nutr. 143: 93–99, 2013.
How Different is Different? Criterion and Sensitivity in Face-Space

Not all detectable differences between face images correspond to a change in identity. Here we measure both sensitivity to change and the criterion difference that is perceived as a change in identity. Both measures are used to test between possible similarity metrics. Using a same/different task and the method of constant stimuli criterion is specified as the 50% “different” point (P50) and sensitivity as the difference limen (DL). Stimuli and differences are defined within a “face-space” based on principal components analysis of measured differences in three-dimensional shape. In Experiment 1 we varied views available. Criterion (P50) was lowest for identical full-face view comparisons that can be based on image differences. When comparing across views P50, was the same for a static 45° change as for multiple animated views, although sensitivity (DL) was higher for the animated case, where it was as high as for identical views. Experiments 2 and 3 tested possible similarity metrics. Experiment 2 contrasted Euclidean and Mahalanobis distance by setting PC1 or PC2 to zero. DL did not differ between conditions consistent with Mahalanobis. P50 was lower when PC2 changed emphasizing that perceived changes in identity are not determined by the magnitude of Euclidean physical differences. Experiment 3 contrasted a distance with an angle based similarity measure. We varied the distinctiveness of the faces being compared by varying distance from the origin, a manipulation that affects distances but not angles between faces. Angular P50 and DL were both constant for faces from 1 to 2 SD from the mean, consistent with an angular measure. We conclude that both criterion and sensitivity need to be considered and that an angular similarity metric based on standardized PC values provides the best metric for specifying what physical differences will be perceived to change in identity.
Loss of animal seed dispersal increases extinction risk in a tropical tree species due to pervasive negative density dependence across life stages

Overhunting in tropical forests reduces populations of vertebrate seed dispersers. If reduced seed dispersal has a negative impact on tree population viability, overhunting could lead to altered forest structure and dynamics, including decreased biodiversity. However, empirical data showing decreased animal-dispersed tree abundance in overhunted forests contradict demographic models which predict minimal sensitivity of tree population growth rate to early life stages. One resolution to this discrepancy is that seed dispersal determines spatial aggregation, which could have demographic consequences for all life stages. We tested the impact of dispersal loss on population viability of a tropical tree species, Miliusa horsfieldii, currently dispersed by an intact community of large mammals in a Thai forest. We evaluated the effect of spatial aggregation for all tree life stages, from seeds to adult trees, and constructed simulation models to compare population viability with and without animal-mediated seed dispersal. In simulated populations, disperser loss increased spatial aggregation by fourfold, leading to increased negative density dependence across the life cycle and a 10-fold increase in the probability of extinction. Given that the majority of tree species in tropical forests are animal-dispersed, overhunting will potentially result in forests that are fundamentally different from those existing now.
Spectral Methods - Part 1: A fast and accurate approach for solving nonlinear diffusive problems

This paper proposes the use of the Spectral method to simulate diffusive moisture transfer through porous materials, which can be strongly nonlinear and can significantly affect sensible and latent heat transfer. An alternative way for computing solutions by considering a separated representation is presented, which can be applied to both linear and nonlinear diffusive problems, considering highly moisture-dependent properties. The Spectral method is compared with the classical implicit Euler and Crank-Nicolson schemes. The results show that the Spectral approach enables to accurately simulate the field of interest. Furthermore, the numerical gains become particularly interesting for nonlinear cases since the proposed method drastically can reduce the computer run time by 99% when compared to the traditional Crank-Nicolson scheme.
missMethyl: an R package for analyzing data from Illumina's HumanMethylation450 platform

UNLABELLED DNA methylation is one of the most commonly studied epigenetic modifications due to its role in both disease and development. The Illumina HumanMethylation450 BeadChip is a cost-effective way to profile >450 000 CpGs across the human genome, making it a popular platform for profiling DNA methylation. Here we introduce missMethyl, an R package with a suite of tools for performing normalization, removal of unwanted variation in differential methylation analysis, differential variability testing and gene set analysis for the 450K array. AVAILABILITY AND IMPLEMENTATION missMethyl is an R package available from the Bioconductor project at www.bioconductor. org. CONTACT alicia.oshlack@mcri.edu. au SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Automatic Detection and Classification of Pole-Like Objects for Urban Cartography Using Mobile Laser Scanning Data

Mobile laser scanning (MLS) is a modern and powerful technology capable of obtaining massive point clouds of objects in a short period of time. Although this technology is nowadays being widely applied in urban cartography and 3D city modelling, it has some drawbacks that need to be avoided in order to strengthen it. One of the most important shortcomings of MLS data is concerned with the fact that it provides an unstructured dataset whose processing is very time-consuming. Consequently, there is a growing interest in developing algorithms for the automatic extraction of useful information from MLS point clouds. This work is focused on establishing a methodology and developing an algorithm to detect pole-like objects and classify them into several categories using MLS datasets. The developed procedure starts with the discretization of the point cloud by means of a voxelization, in order to simplify and reduce the processing time in the segmentation process. In turn, a heuristic segmentation algorithm was developed to detect pole-like objects in the MLS point cloud. Finally, two supervised classification algorithms, linear discriminant analysis and support vector machines, were used to distinguish between the different types of poles in the point cloud. The predictors are the principal component eigenvalues obtained from the Cartesian coordinates of the laser points, the range of the Z coordinate, and some shape-related indexes. The performance of the method was tested in an urban area with 123 poles of different categories. Very encouraging results were obtained, since the accuracy rate was over 90%.
The influence of variables on Boolean functions

Methods from harmonic analysis are used to prove some general theorems on Boolean functions. These connections with harmonic analysis viewed by the authors are very promising; besides the results on Boolean functions they enable them to prove theorems on the rapid mixing of the random walk on the cube and in the extremal theory of finite sets. <<ETX>>
Partial abandonment as an exit strategy for troubled IT projects: Lessons from a small-and-medium enterprise

Purpose – The purpose of this paper is to conduct a stakeholder analysis to find out what factors contribute to partial abandonment and also to examine stakeholders' roles and role conflicts in a partial abandonment implementation process.Design/methodology/approach – A case study of a partially abandoned electronic procurement system project is discussed and analyzed within a small‐and‐medium enterprise in Australia. Semi‐structured interviews, on‐site observation and documentation were the data collection method adopted in this study.Findings – Based on the findings derived from the study, this paper proposes a stakeholder assessment framework of partial abandonment to examine stakeholders' roles and role conflicts in influencing organizational decisions to partially abandon troubled IT projects.Originality/value – The framework will help both researchers and practitioners to shed light on stakeholder‐related issues of partial abandonment, as it offers the flexibility to accommodate understanding of var.
A Framework Supporting the Utilization of Domain Knowledge Embedded in Software

Software systems embed in them knowledge about the domain in which they operate. However, this knowledge is "latent". Making such knowledge accessible could be of great value to the organization both as a source of explicit knowledge and to systems development and maintenance. We propose a framework aimed at making domain knowledge embedded in software explicit. The framework is based on identifying domain knowledge acquired during the development process (especially in requirements analysis) and formalizing it. The software architecture is then partitioned into two parts: one represents the domain knowledge and the other responsible for the actual processing (using this knowledge). A specific object-oriented design approach is suggested to accomplish this partitioning.