Miracle-dz/UniFAR-FTUs huggingface dataset:
An Approach of Fault Diagnosis Using Meta-Heuristics: a New Variant of the Differential Evolution Algorithm

This paper presents an application of meta-heuristics to fault diagnosis. The idea behind this application is to develop methods for fault diagnosis that should be robust, sensitive and with an adequate computational cost. Applications of meta-heuristics are possible based on the formulation of fault diagnosis as an optimization problem. The results indicate the suitability of the use of meta-heuristics for fault diagnosis. In particular, this study shows an application of meta-heuristic termed Differential Evolution to diagnosing a DC Motor benchmark. This allowed developing a new variant of Differential Evolution, namely, Differential Evolution with Particle Collision. This new algorithm was validated with some benchmark functions for continuous optimization, showing that it over-performed the behavior of Differential Evolution.
American Journal of Epidemiology Original Contribution Diet, Supplement Use, and Prostate Cancer Risk: Results from the Prostate Cancer Prevention Trial

The authors examined nutritional risk factors for prostate cancer among 9,559 participants in the Prostate Cancer Prevention Trial (United States and Canada, 1994–2003). The presence or absence of cancer was determined by prostate biopsy, which was recommended during the trial because of an elevated prostate-specific antigen level or an abnormal digital rectal examination and was offered to all men at the trial's end. Nutrient intake was assessed using a food frequency questionnaire and a structured supplement-use questionnaire. Cancer was detected in 1,703 men; 127 cancers were high-grade (Gleason score 8–10). There were no associations of any nutrient or supplement with prostate cancer risk overall. Risk of high-grade cancer was associated with high intake of polyunsaturated fats (quartile 4 vs. quartile 1: odds ratio ¼ 2.41, 95% confidence interval (CI): 1.33, 4.38). Dietary calcium was positively associated with low-grade cancer but inversely associated with high-grade cancer (for quartile 4 vs. quartile 1, odds ratios were 1.27 (95% CI: 1.02, 1.57) and 0.43 (95% CI: 0.21, 0.89), respectively). Neither dietary nor supplemental intakes of nutrients often suggested for prostate cancer prevention, including lycopene, long-chain n-3 fatty acids, vitamin D, vitamin E, and selenium, were significantly associated with cancer risk. High intake of n-6 fatty acids, through their effects on inflammation and oxidative stress, may increase prostate cancer risk. Sound biologic reasoning underlies the hypothesis that dietary patterns, through their effects on steroid hormone and xenobiotic metabolism, oxidative stress, and inflammation , can modify prostate cancer risk. However, the findings from observational and experimental studies examining diet and prostate cancer risk are inconsistent. For example, several cohort studies and secondary analyses from random-ized clinical trials found inverse associations of selenium and vitamin E supplementation with prostate cancer risk (1, 2), often restricted to subsets of men such as smokers (3) or men with specific genotypes (4), but a large random-ized clinical trial did not find reduced risks after supplemen-tation with vitamin E, selenium, or both (5). Inverse associations found for dietary lycopene in some cohorts (6, 7) have not been consistently corroborated in studies using serum lycopene as a biomarker of intake (8, 9). Both dietary and supplemental calcium have been associated with increased risk in many observational studies (10, 11), but calcium supplementation was found to be protective in a randomized clinical trial (12). Many factors could explain the discrepancies across these studies. Most important is the widespread adoption of prostate-specific antigen …
Evaluation of Paraoxonase, Arylesterase and Malondialdehyde Levels in Schizophrenia Patients Taking Typical, Atypical and Combined Antipsychotic Treatment

Objective Human serum paraoxonase (PON1) prevents lipids from peroxidation and functions as an antioxidant mechanism. Malonyldialdehyde (MDA) is the final product of lipid peroxidation and can be used as an indicator of oxidative stress. The aim of this study was to investigate PON1, MDA, and arylesterase (ARY) levels in schizophrenic patients who are taking typical, atypical, or combined (typical and atypical) antipsychotic drug treatment, with respect to those of healthy controls. Methods We evaluated 41 patients (11 taking typical antipsychotics, 19 taking atypical antipsychotics, 11 taking combined anti-psychotics) and 43 healthy controls. Results MDA levels were higher in schizophrenic patients taking typical antipsychotics compared with healthy controls (p=0.001). ARY levels were higher in patients taking atypical antipsychotics compared with healthy controls (p=0.005). PON1 activity was similar in all groups. Conclusion Our results indicate that treatment with typical antipsychotic drugs could be related to increased MDA levels; and antipsychotic medication may increase PON1 levels in schizophrenic patients.
Genomic Transition to Pathogenicity in Chytrid Fungi

Understanding the molecular mechanisms of pathogen emergence is central to mitigating the impacts of novel infectious disease agents. The chytrid fungus Batrachochytrium dendrobatidis (Bd) is an emerging pathogen of amphibians that has been implicated in amphibian declines worldwide. Bd is the only member of its clade known to attack vertebrates. However, little is known about the molecular determinants of - or evolutionary transition to - pathogenicity in Bd. Here we sequence the genome of Bd's closest known relative - a non-pathogenic chytrid Homolaphlyctis polyrhiza (Hp). We first describe the genome of Hp, which is comparable to other chytrid genomes in size and number of predicted proteins. We then compare the genomes of Hp, Bd, and 19 additional fungal genomes to identify unique or recent evolutionary elements in the Bd genome. We identified 1,974 Bd-specific genes, a gene set that is enriched for protease, lipase, and microbial effector Gene Ontology terms. We describe significant lineage-specific expansions in three Bd protease families (metallo-, serine-type, and aspartyl proteases). We show that these protease gene family expansions occurred after the divergence of Bd and Hp from their common ancestor and thus are localized to the Bd branch. Finally, we demonstrate that the timing of the protease gene family expansions predates the emergence of Bd as a globally important amphibian pathogen.
Cellular Responses Evoked by Different Surface Characteristics of Intraosseous Titanium Implants

The properties of biomaterials, including their surface microstructural topography and their surface chemistry or surface energy/wettability, affect cellular responses such as cell adhesion, proliferation, and migration. The nanotopography of moderately rough implant surfaces enhances the production of biological mediators in the peri-implant microenvironment with consequent recruitment of differentiating osteogenic cells to the implant surface and stimulates osteogenic maturation. Implant surfaces with moderately rough topography and with high surface energy promote osteogenesis, increase the ratio of bone-to-implant contact, and increase the bonding strength of the bone to the implant at the interface. Certain features of implant surface chemistry are also important in enhancing peri-implant bone wound healing. It is the purpose of this paper to review some of the more important features of titanium implant surfaces which have an impact on osseointegration.
A Comparison of LAD and OLS Regression for Effort Prediction of Software Projects

Accurate effort prediction of software projects is of concern to portfolio managers, customers, vendors as well as project managers. Ordinary least squares (OLS) regression is widely used to create software prediction models, and it seems to perform just as well or better than most other, non-regression, prediction models. Software data sets may however exhibit certain characteristics that do not always comply with the requirements of OLS. In particular, we may suspect industrial software data sets to be messy due to the cost and difficulty of gathering data. Thus, we should probably be prepared to expect the distribution of residuals to exhibit heavy tails, i.e. high kurtosis, and to be skewed. Under these circumstances, OLS regression may be less efficient than certain robust regression methods. In particular, it can be shown that the Least Absolute Deviation (LAD) regression method is more efficient than OLS when the distribution of the residuals exhibits high kurtosis. In general, it is also useful to apply more than one method to confirm that the initial model specification and results are reasonable. In this paper, we investigate empirically if LAD is more efficient than OLS on a data set of 87 ERP projects. The results suggest that: i) for this particular data set, LAD does not seem more efficient than OLS, ii) LAD does, however, confirm the initial OLS prediction model.
Progressive Hulls for Intersection Applications

Progressive meshes are an established tool for triangle mesh simplification. By suitably adapting the simplification process, progressive hulls can be generated which enclose the original mesh in gradually simpler, nested meshes. We couple progressive hulls with a selective refinement framework and use them in applications involving intersection queries on the mesh. We demonstrate that selectively refinable progressive hulls considerably speed up intersection queries by efficiently locating intersection points on the mesh. Concerning the progressive hull construction, we propose a new formula for assigning edge collapse priorities that significantly accelerates the simplification process, and enhance the existing algorithm with several conditions aimed at producing higher quality hulls. Using progressive hulls has the added advantage that they can be used instead of the enclosed object when a lower resolution of display can be tolerated, thus speeding up the rendering process.
On the use of Convolutional Neural Networks for Pedestrian Detection

In recent years, Deep Learning has emerged showing outstanding results for many different problems related to computer vision, machine learning and speech recognition. In this paper, we study the possibilities to apply convolutional neural networks (CNNs) and explore their power to address the pedestrian detection problem in the context of autonomous driving. We focus on creating a simple and robust framework based on the combination of a CNN architecture and a fast linear classifier. We show how the combination of these ingredients leads to a very accurate classifier, overcoming widespread techniques such as the HOG pedestrian detector and reaching state-of-the-art performance. Results from the wide range of experiments performed are analysed and compared on INRIA, one of the reference datasets for pedestrian detection.
The VMC survey: I. Strategy and first data

Context. The new VISual and Infrared Telescope for Astronomy (VISTA) has started operations. Over its first five years it will be col lecting data for six Public Surveys, one of which is the near-infrared Y JKs VISTA survey of the Magellanic Clouds system (VMC). This survey comprises the Large Magellanic Cloud (LMC), the Small Magellanic Cloud, the Magellanic Bridge connecting the two galaxies and two fields in the Magellanic Stream. Aims. This paper provides an overview of the VMC survey strategy and presents first science results. The main goals of the VMC sur vey are the determination of the spatially-resolved star-form ation history and the three-dimensional structure of the Magellanic system. The VMC survey is therefore designed to reach stars as faint as the ol dest main sequence turn-off point and to constrain the mean magnitude of pulsating variables such as RR Lyrae stars and Cepheids. This paper focuses on observations of VMC fields in the LMC obtained between November 2009 and March 2010. These observations correspond to a completeness of 7% of the planned LMC fields. Methods. The VMC data are comprised of multi-epoch observations which are executed following specific time constraints. The data were reduced using the VISTA Data Flow System pipeline with source catalogues, including astrometric and photometric corrections, produced and made available via the VISTA Science Archive. The VMC data will be released to the astronomical community following the European Southern Observatory’s Public Survey policy. The analysis of the data shows that the sensitivity in each wave band agrees with expectations. Uncertainties and completeness of the data are also derived. Results. The first science results, aimed at assessing the scientific q uality of the VMC data, include an overview of the distribution of stars in colour-magnitude and colour-colour diagrams, the detection of planetary nebulae and stellar clusters, and the Ks band light-curves of variable stars. Conclusions. The VMC survey represents a tremendous improvement, in spatial resolution and sensitivity, on previous panoramic observations of the Magellanic system in the near-infrared, providing a powerful complement to deep observations at other wavelengths.
Skill Management in Large‐Scale Service Marketplaces

Large‐scale, web‐based service marketplaces have recently emerged as a new resource for customers who need quick resolutions for their short‐term problems. Due to the temporary nature of the relations between customers and service providers (agents) in these marketplaces, customers may not have an opportunity to assess the ability of an agent before their service completion. On the other hand, the moderating firm has a more sustained relationship with agents, and thus it can provide customers with more information about the abilities of agents through skill screening mechanisms. In this study, we consider a marketplace where the moderating firm can run two skills tests on agents to assess if their skills are above certain thresholds. Our main objective is to evaluate the effectiveness of skill screening as a revenue maximization tool. We, specifically, analyze how much benefit the firm obtains after each additional skill test. We find that skill screening leads to negligible revenue improvements in marketplaces where agent skills are highly compatible and the average service times are similar for all customers. As the compatibility of agent skills weakens or the customers start to vary in their processing time needs, we show that the firm starts to experience sizable improvements in revenue from skill screening. Apparently, the firm can reap the most of these substantial benefits when it runs only one test. For instance, in marketplaces where agents posses uncorrelated skills, the second skill test only brings an additional 2% improvement in revenue. Accounting for possible skill screening costs, we then show the optimality of offering only one test when the compatibility between agent skills is sufficiently low. The results of this study also have important implications in terms of the right level of intervention in the marketplaces we study.
Ionic Currents Underlying Developmental Regulation of Repetitive Firing in Aplysia Bag Cell Neurons

We have investigated the developmental regulation of the ability to fire repetitively in the bag cell neurons of Aplysia californica, a neuronal system in which the behavioral effects of repetitive firing are well characterized. Adult bag cell neurons exhibit an afterdischarge, consisting of prolonged depolarization and repetitive firing, which causes the release of several peptides from these neurons that induce egg-laying behaviors. Afterdischarge can be triggered in vitro by a variety of stimuli, including electrical stimulation and exposure to the potassium channel blocker tetraethyl ammonium chloride (TEA). In contrast to adults, juvenile neurons did not exhibit afterdischarge in response to pleural–abdominal connective shock or TEA. Juvenile neurons did exhibit, however, prolonged depolarizations in the presence of TEA, perhaps reflecting the anlage of the mechanism responsible for afterdischarge in the adult. To investigate developmental mechanisms underlying the regulation of repetitive firing, we compared ionic currents in adult and juvenile bag cell neurons. We found that during the period in which these neurons acquire the capacity to fire repetitively, a number of currents are regulated: (1) three K+ currents decrease (Ca2+-dependent K+ and two components of voltage-dependent delayed-rectifier K+ current); (2) A-type K+ current increases; and (3) two Ca2+ currents increase (basal and PKC-activated). This pattern is consistent with the increase in the ability to fire repetitively that we observe during maturation: our results indicate that developmental control of repetitive firing in this system is accompanied by selective regulation of specific ionic currents which, after maturation, play important roles in generating the afterdischarge and triggering egg-laying behaviors.
Endogenous Market Structures and Financial Development

Existing theories that emphasize the significance of financial intermediation for economic development have not addressed two important empirical facts: (i) the relationship between financial and real activities depends crucially on the stage of development, and (ii) financial and industrial market structures vary widely across otherwise similar countries. To explain these observations, we develop a dynamic general equilibrium model allowing for endogenous market structures in which financial deepening spurs real activity through intermediate product broadening. We show the possibility of multiple steady-state equilibria and characterize how these equilibria respond to various shocks. In particular, we examine the determinants of financial deepening, product broadening, the saving rate, the loan-deposit interest rate spread, and the degree of competitiveness of financial and product markets. We find that the dynamic interactions between financial and real activities depend critically on the synergy of financial and industrial competitiveness.
Hubble Space Telescope Imaging of the Ultracompact Blue Dwarf Galaxy HS 0822+3542: An Assembling Galaxy in a Local Void?

We present deep U-band, narrow V-band, and I-band images and photometry of the ultracompact blue dwarf galaxy HS 0822+3542 obtained with the Advanced Camera for Surveys/High Resolution Channel of the Hubble Space Telescope. This object is also extremely metal-poor [12 + log(O/H) = 7.45] and resides in a nearby void. The images resolve it into two physically separate components that were previously described as star clusters in a single galaxy. The primary component is only ~100 pc in maximum extent and consists of a starburst region surrounded by a ringlike structure of relatively redder stars. The secondary component is ~50 pc in size and lies at a projected distance of ~80 pc away from the primary, and is also actively star-forming. We estimate masses of ~107 and ~106 M☉ for the two components based on their luminosities, with an associated dynamical timescale for the system of a few megayears. This timescale and the structure of the components suggest that a collision between them triggered their starbursts. The spectral energy distributions of both components can be fitted by the combination of a recent (a few megayears old) starburst and an evolved (several gigayears old) underlying stellar population, similar to larger blue compact dwarf galaxies. This indicates that despite its metal deficiency, the object is not forming its first generation of stars. However, the small sizes and masses of the two components suggest that HS 0822+3542 represents a dwarf galaxy in the process of assembling from clumps of stars intermediate in size between globular clusters and objects previously classified as galaxies. Its relatively high ratio of neutral gas mass to stellar mass (~1) and high specific star formation rate, log(SFR/M☉) ≃ -9.2, also suggest that it is still converting much of its gas to stars.
The Wilms Tumor-1 (WT1) rs16754 polymorphism is a prognostic factor in acute myeloid leukemia (AML): a meta-analysis

Although a number of studies suggested that WT1 rs16754 polymorphism might be related to decreased relapse free survival (RFS) and overall survival (OS). The results remain controversial. Published reports were searched in PubMed, EMBASE, and Google Scholar. Twelve publications with 3903 patients had met the inclusion criteria and were subjected to further examination. We found WT1 rs16754 polymorphism was significantly associated with OS in AML (OR = 0.62; 95% CI 0.52 − 0.75; p < 0.00001; I2 = 47%). WT1 rs16754 polymorphism was also significantly associated with RFS in AML (OR = 0.69; 95% CI 0.57 − 0.83; p < 0.001; I2 = 46%). In the subgroup analyses of age, race, and subtype of AML, WT1 rs16754 polymorphism was a independent favorable-risk marker. In conclusion, WT1 rs16754 polymorphism is associated with better survival of AML. It could be used as a cost-effective prognostic biomarker for AML.
Simultaneous perturbation methods for adaptive labor staffing in service systems

We consider the problem of optimizing the workforce of a service system. Adapting the staffing levels in such systems is non-trivial due to large variations in workload and the large number of system parameters do not allow for a brute force search. Further, because these parameters change on a weekly basis, the optimization should not take longer than a few hours. Our aim is to find the optimum staffing levels from a discrete high-dimensional parameter set, that minimizes the long run average of the single-stage cost function, while adhering to the constraints relating to queue stability and service-level agreement (SLA) compliance. The single-stage cost function balances the conflicting objectives of utilizing workers better and attaining the target SLAs. We formulate this problem as a constrained parameterized Markov cost process parameterized by the (discrete) staffing levels. We propose novel simultaneous perturbation stochastic approximation (SPSA)-based algorithms for solving the above problem. The algorithms include both first-order as well as second-order methods and incorporate SPSA-based gradient/Hessian estimates for primal descent, while performing dual ascent for the Lagrange multipliers. Both algorithms are online and update the staffing levels in an incremental fashion. Further, they involve a certain generalized smooth projection operator, which is essential to project the continuous-valued worker parameter tuned by our algorithms onto the discrete set. The smoothness is necessary to ensure that the underlying transition dynamics of the constrained Markov cost process is itself smooth (as a function of the continuous-valued parameter): a critical requirement to prove the convergence of both algorithms. We validate our algorithms via performance simulations based on data from five real-life service systems. For the sake of comparison, we also implement a scatter search based algorithm using state-of-the-art optimization tool-kit OptQuest. From the experiments, we observe that both our algorithms converge empirically and consistently outperform OptQuest in most of the settings considered. This finding coupled with the computational advantage of our algorithms make them amenable for adaptive labor staffing in real-life service systems.