Miracle-dz/UniFAR-FTUs huggingface dataset:
Work/family balance: HRM policy and practice in Australia

An employee's inability to balance work and family responsibilities has resulted in an increase in stress related illnesses. Historically, research into the nexus between work and family has primarily focused on the work/family conflict relationship, predominately investigating the impact of this conflict on parents, usually mothers. To date research has not sufficiently examined the human resource management practices that enable all parents to achieve a balance between their work and family lives. This paper explores the relationship between contemporary family friendly HRM policies and employed parents perceptions of work/family enhancement, work/family satisfaction, propensity to turnover, and work/family conflict. Self-report questionnaire data from 326 men and women is analysed and discussed to enable organisations to consider the use of family friendly policies and thus create a convergence between the well-being of employees and the effectiveness of the organisation.
Cognitive radio: Ten years of experimentation and development

The year 2009 marked the 10th anniversary of Mitola and Maguire Jr. introducing the concept of cognitive radio. This prompted an outpouring of research work related to CR, including the publication of more than 30 special issue scientific journals and more than 60 dedicated conferences and workshops. Although the theoretical research is blooming, with many interesting results presented, hardware and system development for CR is progressing at a slower pace. We provide synopses of the commonly used platforms and testbeds, examine what has been achieved in the last decade of experimentation and trials relating to CR, and draw several perhaps surprising conclusions. This analysis will enable the research community to focus on the key technologies to enable CR in the future.
Multi-grid transformation for medical image registration

It is an enormous challenge to register different physical brain images to each other, or to register a set of brain images from different modalities such as CT, MRI, SPECT, and PET. Image registration is the process of aligning the different sets of data of the same object into a common coordinate system thus aligning them in order to analyze subtle changes among each other. This study proposes a new approach of registration for brain images based on Multi-Grid Transformation. The novelty of the method is that the correlation of functional brain image data obtained from different individuals can be achieved by registration of the corresponding anatomical brain images using the smart transition of grid. The Bilinear and Affine Transformations have been used in order to maintain geometric alignment throughout the process. The major benefit of the study involves integrating the images to create a composite view, extracting information that would be impossible to obtain from a single image. Therefore, the doctor can observe the variety of brain scanned images to do the diagnosis and therapy planning for clinical analysis at the same time.
THE CONTROL OF CHAOS: THEORETICAL SCHEMES AND EXPERIMENTAL REALIZATIONS

Controlling chaos is a process wherein an unstable periodic orbit embedded in a chaotic attractor is stabilized by means of tiny perturbations of the system. These perturbations imply goal oriented feedback techniques which act either on the state variables of the system or on the control parameters. We review some theoretical schemes and experimental implementations for the control of chaos.
A Study on Flexibility of ERP System Based on Grey Evaluation Model

the competitive environment and changing business processes propose new requirements to ERP system's flexibility and its evaluation becomes the first and critical step to solve these problems. This paper begins with the analysis of flexibility's definition.Basing on the core idea of three-tier software architecture,the author refines the index system from the aspects of presentation flexibility, business flexibility and design flexibility. Then,treating the grey theory as a guide, the evaluation system is established by integrating AHP and Grey Evaluation Model.Finally,the corresponding example is given to illustrate the model.
Laparoscopic Hepatectomy for Hepatic Colorectal Metastases – A Retrospective Comparative Cohort Analysis and Literature Review

Background Laparoscopic hepatectomy (LH) for management of hepatic colorectal metastases (HCRM) is commonly being performed; however, there are limited reports comparing LH outcomes with those of open hepatectomy (OH) procedure. The aim of the present study was to compare perioperative outcomes between the LH and OH procedures performed at a single medical center. Methods From Jan 2008 to May 2012, 30 patients with pathologically confirmed HCRM underwent LH, and 140 patients underwent OH at our hospital. Patients' demographics, perioperative outcomes were retrospectively analyzed. Results 2 patients (6.7%) in the LH group underwent laparotomies for intraoperative hemorrhage. The LH group had an increased surgical duration (235 min vs. 365 min, (P<0.001), shorter hospital stay (7.5 days vs. 11.5 days, P<0.001), and fewer complications (26.2% vs. 55%, P<0.001) than the OH group. However, in a matched cohort comparison of 30 LH cases and 30 OH cases, no significant variations were observed in the following parameters: surgical duration (235 min vs. 255 min, P = 0.23), positive margin rates (6.7% vs. 0.0%, P = 0.27), or postoperative hematological changes. LH patients had less estimated blood loss (215 ml vs. 385 ml, P<0.001), less morbidity (26.2% vs. 50%, P = 0.02), shorter hospital stay (7.5 days vs. 11.5 days, P<0.001), and lower analgesic requests than with those in the OH group. Conclusions LH for metastatic colorectal cancer is a safe and feasible treatment, even in patients who underwent prior laparotomy surgeries and provides significantly less morbidity and shorter hospital stay than OH, without compromising curability or increasing morbidity.
A meta-analysis of natural resources and conflict

The relationship between natural resource wealth and civil conflict remains unclear, despite prolonged scholarly attention. Conducting a meta-analysis—a quantitative literature review—can help synthesize this broad and disparate field to provide clearer directions for future research. Meta-analysis tools determine both the aggregate effect of natural resources on conflict and whether any particular ways in which variables are measured systematically bias the estimated effect. I conduct a meta-analysis using sixty-nine studies from sixty-two authors. I find that there is no aggregate relationship between natural resources and conflict. Most variation in variable measurement does not alter the estimated effect. However, measuring natural resource wealth using Primary Commodity Exports and including controls for mountainous terrain and ethnic fractionalization all do significantly impact the results. These findings suggest that it may be worth exploring more nuanced connections between natural resources and conflict instead of continuing to study the overall relationship.
Relay selection and power allocation for cognitive energy harvesting two-way relaying networks

Energy harvesting (EH) from ambient environment is an attractive and green solution to the problem of limited lifetime of wireless and mobile devices such as cognitive relay nodes. In this paper, we extend the previous works on cognitive two-way relaying network by introducing energy harvesting transceiver nodes that can accumulate energy to improve the lifetime of the relay network. We investigate an optimal offline joint relay selection and power allocation scheme where secondary transceivers and relays are energy harvesting nodes. We put forward an offline optimization problem of the maximization of the amplify-and-forward (AF) cooperative communication system throughput which can be solved by Lagrange function. Numerical results show that the proposed scheme performs better than random relay selection scheme on the restriction of transmit power and primary user (PU) interference.
Using Active Filters to Reduce THD in Traction Systems

DC underground traction systems are a powerful source of harmonic distortion, and so, suitable corrective actions have to be taken. For the design of these corrective actions simulation has proved to be a very useful tool. In this paper, the simulation of an active filter for the reduction of the current harmonic distortion of an underground traction system is presented.
Voting-based active contour segmentation of fMRI images of the brain

We propose an algorithm for automated segmentation of white matter in brain MRI images, which can be used to create connected representations of the gray matter in the cerebral cortex of the brain. These representations then provide meaningful visualizations of brain activity data obtained from fMRI studies. Our algorithm to segment the white matter from the rest of the image is based on an active-contour scheme - STACS, and thus inherits all the advantages active-contour schemes possess. The segmentation, performed in three different planes of image capture, is driven by the statistics of the image. We combine the segmentation results from the three planes by a majority voting procedure to classify each voxel in the image as white matter or not. We improve the runtime of the algorithm by rewriting the force computation as a multiscale transformation. Initial results of labeling the white matter with an accuracy of about 89% show great promise of the proposed algorithm.
How random are a learner's mistakes?

Given a random binary sequence $X^{(n)}$ of random variables, $X_{t},$ $t=1,2,. ,n$, for instance, one that is generated by a Markov source (teacher) of order $k^{*}$ (each state represented by $k^{*}$ bits). Assume that the probability of the event $X_{t}=1$ is constant and denote it by $\beta$. Consider a learner which is based on a parametric model, for instance a Markov model of order $k$, who trains on a sequence $x^{(m)}$ which is randomly drawn by the teacher. Test the learner's performance by giving it a sequence $x^{(n)}$ (generated by the teacher) and check its predictions on every bit of $x^{(n)}. $ An error occurs at time $t$ if the learner's prediction $Y_{t}$ differs from the true bit value $X_{t}$. Denote by $\xi^{(n)}$ the sequence of errors where the error bit $\xi_{t}$ at time $t$ equals 1 or 0 according to whether the event of an error occurs or not, respectively. Consider the subsequence $\xi^{(\nu)}$ of $\xi^{(n)}$ which corresponds to the errors of predicting a 0, i.e., $\xi^{(\nu)}$ consists of the bits of $\xi^{(n)}$ only at times $t$ such that $Y_{t}=0. $ In this paper we compute an estimate on the deviation of the frequency of 1s of $\xi^{(\nu)}$ from $\beta$. The result shows that the level of randomness of $\xi^{(\nu)}$ decreases relative to an increase in the complexity of the learner.
Wavelet-based rotational invariant roughness features for texture classification and segmentation

In this paper, we introduce a rotational invariant feature set for texture segmentation and classification, based on an extension of fractal dimension (FD) features. The FD extracts roughness information from images considering all available scales at once. In this work, a single scale is considered at a time so that textures with scale-dependent properties are satisfactorily characterized. Single-scale features are combined with multiple-scale features for a more complete textural representation. Wavelets are employed for the computation of single- and multiple-scale roughness features because of their ability to extract information at different resolutions. Features are extracted in multiple directions using directional wavelets, and the feature vector is finally transformed to a rotational invariant feature vector that retains the texture directional information. An iterative K-means scheme is used for segmentation, and a simplified form of a Bayesian classifier is used for classification. The use of the roughness feature set results in high-quality segmentation performance. Furthermore, it is shown that the roughness feature set exhibits a higher classification rate than other feature vectors presented in this work. The feature set retains the important properties of FD-based features, namely insensitivity to absolute illumination and contrast.
Sweet liking and high novelty seeking: independent phenotypes associated with alcohol-related problems.

AIM We tested the hypothesis that high novelty seeking (NS; a trait that promotes experimentation) and hedonic response to sweet taste (a trait that may reflect processing of hedonic stimuli) act independently to increase the risk for having alcohol-related problems in young adults. METHODS The study was conducted in 158 healthy subjects (age 20-25 years) with no lifetime history of alcohol and/or drug abuse/dependence. NS was evaluated using the Tridimensional Personality Questionnaire. Pleasurable response to sweet taste was tested, using a sweet taste test to identify sweet likers (SL; those preferring the strongest offered sucrose solution) and sweet dislikers (SDL; those preferring weaker sucrose solutions). RESULTS NS score, but not SL/SDL status, was positively correlated with drinks per month (P = 0.0054) and drinks per drinking day (P = 0.021). When tested individually, both NS and SL/SDL status predict having alcohol-related problems (NS: odds ratio [OR] = 5.3, P = 0.0016 and SL/SDL: OR = 5.8, P = 0.0001) with an OR similar to positive family history of alcoholism status (OR = 5.7, P = 0.0007). The combination of SL status and high NS score (greater than gender-specific 70th percentile) greatly increased the estimated odds of having alcohol-related problems (OR 27.5, P < 0.0001). CONCLUSIONS These results support the hypothesis that high NS and SL phenotypes are independently associated with risk of alcohol-related problems. The combination of both phenotypes greatly increases the likelihood of alcohol-related problems. Although confirmation is necessary, this suggests that these phenotypes could contribute to improved methods to assess risk for alcohol-related problems and provide additional insight into processes underlying progression to alcohol-related problems.
Author Profiling Using Corpus Statistics, Lexicons and Stylistic Features Notebook for PAN at CLEF-2013

This paper describes our participation in the 9th PAN eval- uation lab in the author proling task. The proposed approach relies on the extraction of stylistic, lexicon and corpus-based features, which were combined with a logistic classier. These three sets of features contain pairwise intersections and even some features that belong to all cate- gories. A comprehensive comparison of the contribution of several feature subsets is presented. In particular, a set of features based on Bayesian inference provided the most important contribution. We developed our system in the Spanish training corpus, once developed it was used, with minor changes, for the English documents, too. The proposed system was ranked 6th in the ocial ranking for Spanish documents among 17 submitted systems. This result shows that our approach is meaningful and competitive for predicting demographics from text.
Generalized Ricci curvature based sampling and reconstruction of images

We introduce a novel method of image sampling based on viewing grayscale images as manifolds with density, and sampling them according to the generalized Ricci curvature introduced by Bakry, Emery and Ledoux. A variation of this approach, due to Morgan and his students is also considered. This new paradigm generalizes ideas and results that are by now common in Imaging and Graphics. We apply the new algorithm to natural and range images, as well as cartoons and show that the proposed method produces results similar to those obtained by employing more standard approaches. Furthermore, we show that our approach extends naturally to other types of images, in particular to MRI and CT, where its potential applications are maximal, as well as to meshes.
Path Deformation Roadmaps: Compact Graphs with Useful Cycles for Motion Planning

In this paper we describe a new approach to sampling-based motion planning with Probabilistic Roadmap Planner (PRM) methods. Our aim is to compute good quality roadmaps which encode the multiple connectedness of the configuration space inside small but yet representative graphs which capture the different varieties of free paths well. The proposed Path Deformation Roadmaps (PDRs) rely on a notion of path deformability indicating whether or not a given path can be continuously deformed into another existing path. By considering a simpler form of deformation than that allowed between homotopic paths, we propose a method that extends the Visibility-PRM technique to construct compact roadmaps which encode richer and more suitable information than representative paths of the homotopy classes. PDRs contain additional useful cycles between paths in the same homotopy class that can be hardly deformed into each other. Experimental results show that the technique enables small roadmaps to reliably capture the multiple connectedness of complex spaces in various problems involving free-flying and articulated robots in both two- and three-dimensional environments.
Using Wicked problems to foster interdisciplinary practice among UK trainee teachers

ABSTRACT An uncertain world characterised by the complexity associated with ‘Wicked’ problems presents formidable challenges for the preparation of teachers. This paper reports on one cycle in a larger action research project in which subject specialist trainee teachers worked in inter-disciplinary groups to design and run classroom-based workshops on climate change for pupils aged 12–14. While the project sought to explore interdisciplinary working, subject specialisms and their values were not abandoned, recognising that diversity can lead to more powerful, collective knowledge being generated. The Wicked problem of climate change was initially examined from different subject perspectives, identifying the opportunities that the work afforded in each subject, along with the challenges that accompanied them. The findings suggest that trainee teachers valued the collaboration and the opportunity to develop different pedagogical approaches used by different subjects. The framing of the project around a Wicked problem supported trainee teachers in understanding that no one subject had an authoritative prerogative over the topic while the disquiet that the interdisciplinary project provoked, in some cases, served to instigate new transformative learning which stretched beyond traditional disciplinary boundaries.
Automatic singer recognition of popular music recordings via estimation and modeling of solo vocal signals

In this paper, we investigate the problem of automatic singer identification, detection and tracking in popular music recordings with one or multiple singers. This problem reflects an important issue in multimedia applications that require the transcription and indexing of music data to meet the increasing demand for content-based information retrieval. The major challenges for this study arise from the fact that a singer's voice tends to be arbitrarily altered from time to time and is inextricably intertwined with the signal of the background accompaniment. To determine who is singing, or whether or when a particular singer is present in a music recording, methods are presented for separating vocal from nonvocal regions, for isolating singers' vocal characteristics from background music, and for distinguishing singers from one another. Experimental evaluations conducted on a pop music database consisting of solo and duet tracks confirm the validity of the proposed methods.
An Analysis of Spatial-and Fourier-Multiplexed Imaging

Multiplexing is a common technique for encoding highdimensional image data into a single two-dimensional image. Examples of spatial multiplexing include Bayer patterns to encode color channels, and integral images to encode light fields. In the Fourier domain, optical heterodyning has been used to encode light fields. In this paper, we analyze the relationship between spatial and Fourier multiplexing techniques. We develop this analysis on the example of multi-spectral imaging, and then generalize it to light fields and other properties. We also analyze the effects of sensor saturation on Fourier multiplexing techniques such as optical heterodyning, and devise a new optimization approach for recovering saturated detail. CR Categories: I.4. 1 [IMAGE PROCESSING AND COMPUTER VISION]: Digitization and Image Capture;
Trypanosomosis: potential driver of selection in African cattle

Trypanosomosis is a serious cause of reduction in productivity of cattle in tsetse-fly infested areas. Baoule and other local Taurine cattle breeds in Burkina Faso are trypanotolerant. Zebuine cattle, which are also kept there are susceptible to trypanosomosis but bigger in body size. Farmers have continuously been intercrossing Baoule and Zebu animals to increase production and disease tolerance. The aim of this study was to compare levels of zebuine and taurine admixture in genomic regions potentially involved in trypanotolerance with background admixture of composites to identify differences in allelic frequencies of tolerant and non-tolerant animals. The study was conducted on 214 animals (90 Baoule, 90 Zebu, and 34 composites), genotyped with 25 microsatellites across the genome and with 155 SNPs in 23 candidate regions. Degrees of admixture of composites were analyzed for microsatellite and SNP data separately. Average Baoule admixture based on microsatellites across the genomes of the Baoule- Zebu composites was 0.31, which was smaller than the average Baoule admixture in the trypanosomosis candidate regions of 0.37 (P = 0.15). Fixation index FST measured in the overall genome based on microsatellites or with SNPs from candidate regions indicates strong differentiation between breeds. Nine out of 23 regions had FST ≥ 0.20 calculated from haplotypes or individual SNPs. The levels of admixture were significantly different from background admixture, as revealed by microsatellite data, for six out of the nine regions. Five out of the six regions showed an excess of Baoule ancestry. Information about best levels of breed composition would be useful for future breeding ctivities, aiming at trypanotolerant animals with higher productive capacity.
Chain Reduction Preserves the Unrooted Subtree Prune-and-Regraft Distance

The subtree prune-and-regraft (SPR) distance metric is a fundamental way of comparing evolutionary trees. It has wide-ranging applications, such as to study lateral genetic transfer, viral recombination, and Markov chain Monte Carlo phylogenetic inference. Although the rooted version of SPR distance can be com puted relatively efficiently between rooted trees using fixed-parameter-tractable algorithms, in the unrooted case previous algorithms are unable to compute distances larger than 7. One important tool for efficient computation in the rooted case is called chain reduction, which replaces an arbitrary chain of subtrees identical in both trees with a chain of three leaves. Whether chain reduction preserves SPR distance in the unrooted case has remained an open question since it was conjectured in 2001 by Allen and Steel, and was presented as a challenge question at the 2007 Isaac Newton Institute for Mathematical Sciences program on phylogenetics. In this paper we prove that chain reduction preserves the unrooted SPR distance. We do so by introducing a structure called a socket agreement forest that restricts edge modification to predetermined socket vertices, permitting detailed analysis and modification of SPR move sequences. This new chain reduction theorem reduces the unrooted distance problem to a linear size problem kernel, substantially improving on the previous best quadratic size kernel.