Miracle-dz/UniFAR-FTUs huggingface dataset:
MAGSAC: Marginalizing Sample Consensus

A method called, sigma-consensus, is proposed to eliminate the need for a user-defined inlier-outlier threshold in RANSAC. Instead of estimating the noise sigma, it is marginalized over a range of noise scales. The optimized model is obtained by weighted least-squares fitting where the weights come from the marginalization over sigma of the point likelihoods of being inliers. A new quality function is proposed not requiring sigma and, thus, a set of inliers to determine the model quality. Also, a new termination criterion for RANSAC is built on the proposed marginalization approach. Applying sigma-consensus, MAGSAC is proposed with no need for a user-defined sigma and improving the accuracy of robust estimation significantly. It is superior to the state-of-the-art in terms of geometric accuracy on publicly available real-world datasets for epipolar geometry (F and E) and homography estimation. In addition, applying sigma-consensus only once as a post-processing step to the RANSAC output always improved the model quality on a wide range of vision problems without noticeable deterioration in processing time, adding a few milliseconds.
Temporal preference in individuals reporting chronic pain: discounting of delayed pain-related and monetary outcomes

Abstract Opioid therapy for pain is associated with an increased risk for substance use disorders. This study's purpose was to determine the association between opioid misuse propensity (Screener and Opioid Assessment for Patients in Pain–Revised) and delay discounting (DD), a behavioral process linked to substance use disorders, which quantifies the extent to which outcomes are devalued because of their delay. Participants reporting chronic pain (N = 249) answered pain and opioid use questions and then completed 4 DD tasks. Each of these tasks assessed either money or pain consequences, framed as either rewards or punishments. Each task involved hypothetical choices between immediate smaller vs delayed larger consequences. The extant Monetary Choice Questionnaire assessed DD of money rewards, and a modified version assessed discounting of money losses (immediate smaller loss vs larger delayed loss). Based on the Monetary Choice Questionnaire, the novel Pain Relief Choice Questionnaire assessed choices between an immediate short duration of pain relief vs a longer duration of pain relief. Similarly, the novel Additional Pain Choice Questionnaire assessed choices between an immediate short duration of additional pain vs a longer duration of additional pain. Discounting of both additional pain and money losses were significantly associated with high Screener and Opioid Assessment for Patients in Pain–Revised scores—indicating participants at greatest risk for opioid misuse discount future punishments rather than future rewards compared with those at low risk. Measures of DD may have promise in more accurately identifying individuals at highest risk for opioid misuse during chronic opioid therapy.
Movardol® (N-acetylglucosamine, Boswellia serrata, ginger) supplementation in the management of knee osteoarthritis: preliminary results from a 6-month registry study.

OBJECTIVE Knee Osteoarthritis (OA) is a chronic disease caused by the deterioration of cartilage in joints, which results in activation of the inflammatory response, pain, and impaired movement. Complementary therapies, particularly supplementation, in the management of moderate/severe knee OA have been gaining attention. This registry study aimed at evaluating the synergistic effect of Movardol®, a supplementation containing active ingredients with recognized anti-inflammatory activities on symptoms and levels of circulating biomarkers of knee OA. PATIENTS AND METHODS 54 subjects with symptomatic, moderate knee OA freely decided to follow either a standard management (SM) (n = 26) or SM plus oral supplementation with Movardol® (n = 28). Movardol® supplementation containing N-acetyl-D-glucosamine, ginger, and Boswellia Serrata extract was taken at the following dosage: 3 tablets/day for one week and then 2 tablets/day. Several parameters were assessed at inclusion and after 1, 3 and 6 months: functional impairment by the Karnofsky Performance Scale Index; pain, stiffness, physical, social and emotional functions by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC); total and pain-free walking distance; circulating biomarkers of inflammation and oxidative stress. RESULTS Significant improvements in the functional outcomes and pain-free walking distance were observed after 1, 3 and 6 months in OA patients supplemented with Movardol®. Moreover, all the signs/symptoms of disease assessed by the WOMAC tended to regress over a 6-month period in patients following SM+supplementation. Inflammatory markers and plasmatic content of reactive oxygen species decreased over 6 months, in supplemented patients. Movardol® supplementation resulted to be safe and well tolerated, also showing the beneficial effect in term of a decrease in pharmacological and non-pharmacological treatments and, consequently, reduction in management costs. CONCLUSIONS These preliminary results indicate the efficacy and safety of Movardol® supplementation in the management of moderate knee OA.
On Sparse Vector Recovery Performance in Structurally Orthogonal Matrices via LASSO

In this paper, we consider the compressed sensing problem of reconstructing a sparse signal from an undersampled set of noisy linear measurements. The regularized least squares or least absolute shrinkage and selection operator (LASSO) formulation is used for signal estimation. The measurement matrix is assumed to be constructed by concatenating several randomly orthogonal bases, which we refer to as structurally orthogonal matrices. Such measurement matrix is highly relevant to large-scale compressive sensing applications because it facilitates rapid computation and parallel processing. Using the replica method in statistical physics, we derive the mean-squared-error (MSE) formula of reconstruction over the structurally orthogonal matrix in the large-system regime. Extensive numerical experiments are provided to verify the analytical result. We then consider the analytical result to investigate the MSE behaviors of the LASSO over the structurally orthogonal matrix, with an emphasis on performance comparisons with matrices with independent and identically distributed (i.i.d.) Gaussian entries. We find that structurally orthogonal matrices are at least as good as their i.i. d. Gaussian counterparts. Thus, the use of structurally orthogonal matrices is attractive in practical applications.
Gap Detection in School-Age Children and Adults: Center Frequency and Ramp Duration.

Purpose The age at which gap detection becomes adultlike differs, depending on the stimulus characteristics. The present study evaluated whether the developmental trajectory differs as a function of stimulus frequency region or duration of the onset and offset ramps bounding the gap. Method Thresholds were obtained for wideband noise (500-4500 Hz) with 4- or 40-ms raised-cosine ramps and for a 25-Hz-wide low-fluctuation narrowband noise centered on either 500 or 5000 Hz with 40-ms ramps. Stimuli were played continuously at 70 dB SPL, and the task was to indicate which of 3 intervals contained a gap. Listeners were 5.2- to 15.1-year-old children (n = 40) and adults (n = 10) with normal hearing. Results Regardless of listener age, gap detection thresholds for the wideband noise tended to be lower when gaps were shaped using 4-ms rather than 40-ms ramps. Thresholds also tended to be lower for the low-fluctuation narrowband noise centered on 5000 Hz than 500 Hz. Performance reached adult levels after 11 years of age for all 4 stimuli. Maturation was not uniform across individuals, however; a subset of young children performed like adults, including some 5-year-olds. Conclusion For these stimuli, the developmental trajectory was similar regardless of narrowband noise center frequency or wideband noise onset and offset ramp duration.
Online Nonlinear AUC Maximization for Imbalanced Data Sets

Classifying binary imbalanced streaming data is a significant task in both machine learning and data mining. Previously, online area under the receiver operating characteristic (ROC) curve (AUC) maximization has been proposed to seek a linear classifier. However, it is not well suited for handling nonlinearity and heterogeneity of the data. In this paper, we propose the kernelized online imbalanced learning (KOIL) algorithm, which produces a nonlinear classifier for the data by maximizing the AUC score while minimizing a functional regularizer. We address four major challenges that arise from our approach. First, to control the number of support vectors without sacrificing the model performance, we introduce two buffers with fixed budgets to capture the global information on the decision boundary by storing the corresponding learned support vectors. Second, to restrict the fluctuation of the learned decision function and achieve smooth updating, we confine the influence on a new support vector to its $k$ -nearest opposite support vectors. Third, to avoid information loss, we propose an effective compensation scheme after the replacement is conducted when either buffer is full. With such a compensation scheme, the performance of the learned model is comparable to the one learned with infinite budgets. Fourth, to determine good kernels for data similarity representation, we exploit the multiple kernel learning framework to automatically learn a set of kernels. Extensive experiments on both synthetic and real-world benchmark data sets demonstrate the efficacy of our proposed approach.
CERA Attenuates Kidney Fibrogenesis in the db/db Mouse by Influencing the Renal Myofibroblast Generation

Tubulointerstitial fibrosis (TIF) is a pivotal pathophysiological process in patients with diabetic nephropathy (DN). Multiple profibrotic factors and cell types, including transforming growth factor beta 1 (TGF-β1) and interstitial myofibroblasts, respectively, are responsible for the accumulation of extracellular matrix in the kidney. Matrix-producing myofibroblasts can originate from different sources and different mechanisms are involved in the activation process of the myofibroblasts in the fibrotic kidney. In this study, 16-week-old db/db mice, a model for type 2 DN, were treated for two weeks with continuous erythropoietin receptor activator (CERA), a synthetic erythropoietin variant with possible non-hematopoietic, tissue-protective effects. Non-diabetic and diabetic mice treated with placebo were used as controls. The effects of CERA on tubulointerstitial fibrosis (TIF) as well as on the generation of the matrix-producing myofibroblasts were evaluated by morphological, immunohistochemical, and molecular biological methods. The placebo-treated diabetic mice showed significant signs of beginning renal TIF (shown by picrosirius red staining; increased connective tissue growth factor (CTGF), fibronectin and collagen I deposition; upregulated KIM1 expression) together with an increased number of interstitial myofibroblasts (shown by different mesenchymal markers), while kidneys from diabetic mice treated with CERA revealed less TIF and fewer myofibroblasts. The mechanisms, in which CERA acts as an anti-fibrotic agent/drug, seem to be multifaceted: first, CERA inhibits the generation of matrix-producing myofibroblasts and second, CERA increases the ability for tissue repair. Many of these CERA effects can be explained by the finding that CERA inhibits the renal expression of the cytokine TGF-β1.
Oyster Larvae Settle in Response to Habitat-Associated Underwater Sounds

Following a planktonic dispersal period of days to months, the larvae of benthic marine organisms must locate suitable seafloor habitat in which to settle and metamorphose. For animals that are sessile or sedentary as adults, settlement onto substrates that are adequate for survival and reproduction is particularly critical, yet represents a challenge since patchily distributed settlement sites may be difficult to find along a coast or within an estuary. Recent studies have demonstrated that the underwater soundscape, the distinct sounds that emanate from habitats and contain information about their biological and physical characteristics, may serve as broad-scale environmental cue for marine larvae to find satisfactory settlement sites. Here, we contrast the acoustic characteristics of oyster reef and off-reef soft bottoms, and investigate the effect of habitat-associated estuarine sound on the settlement patterns of an economically and ecologically important reef-building bivalve, the Eastern oyster (Crassostrea virginica). Subtidal oyster reefs in coastal North Carolina, USA show distinct acoustic signatures compared to adjacent off-reef soft bottom habitats, characterized by consistently higher levels of sound in the 1.5–20 kHz range. Manipulative laboratory playback experiments found increased settlement in larval oyster cultures exposed to oyster reef sound compared to unstructured soft bottom sound or no sound treatments. In field experiments, ambient reef sound produced higher levels of oyster settlement in larval cultures than did off-reef sound treatments. The results suggest that oyster larvae have the ability to respond to sounds indicative of optimal settlement sites, and this is the first evidence that habitat-related differences in estuarine sounds influence the settlement of a mollusk. Habitat-specific sound characteristics may represent an important settlement and habitat selection cue for estuarine invertebrates and could play a role in driving settlement and recruitment patterns in marine communities.
Density-Dependent Effects on Group Size Are Sex-Specific in a Gregarious Ungulate

Density dependence can have marked effects on social behaviors such as group size. We tested whether changes in population density of a large herbivore (elk, Cervus canadensis) affected sex-specific group size and whether the response was density- or frequency-dependent. We quantified the probability and strength of changes in group sizes and dispersion as population density changed for each sex. We used group size data from a population of elk in Manitoba, Canada, that was experimentally reduced from 1.20 to 0.67 elk/km2 between 2002 and 2009. Our results indicated that functional responses of group size to population density are sex-specific. Females showed a positive density-dependent response in group size at population densities ≥0.70 elk/km2 and we found evidence for a minimum group size at population density ≤0.70 elk/km2. Changes in male group size were also density-dependent; however, the strength of the relationship was lower than for females. Density dependence in male group size was predominantly a result of fusion of solitary males into larger groups, rather than fusion among existing groups. Our study revealed that density affects group size of a large herbivore differently between males and females, which has important implications for the benefits e.g., alleviating predation risk, and costs of social behaviors e.g., competition for resources and mates, and intra-specific pathogen transmission.
Association of Dietary Patterns with Components of Metabolic Syndrome and Inflammation among Middle-Aged and Older Adults with Metabolic Syndrome in Taiwan

This study examined the correlation of dietary patterns with components of metabolic syndrome (MetS) and inflammation among middle-aged and older adults with MetS in Taiwan. This cross-sectional study used data from the Mei Jau International Health Management Institution in Taiwan between 2004 and 2013. A total of 26,016 subjects aged 35 years and above were selected for analysis. MetS was defined according to the International Diabetes Federation. Three dietary patterns were identified by principal component analysis. High intake of a meat–instant food dietary pattern (rich in animal protein, saturated fat, sweets, sodium, and food additives) was positively associated with components of MetS and C-reactive protein (CRP), while high intake of a vege–seafood dietary pattern (rich in dietary fiber, vitamins, minerals, and unsaturated fat) or a cereal–dairy dietary pattern (rich in dietary fiber, antioxidants, phytochemicals, complex carbohydrate, prebiotics, and probiotics) was inversely associated with components of MetS and CRP. Our findings suggested that intake of a vege–seafood dietary pattern or a cereal–dairy dietary pattern decreased the risk of developing MetS and inflammation among middle-aged and older adults with MetS.
Improvement of cycloid psychosis following electroconvulsive therapy

Abstract Background: The treatment of choice for cycloid psychosis has traditionally been electroconvulsive therapy (ECT), but there is a lack of studies on its effectiveness. Aims: The primary aim of this register study was to determine the rates of remission and response after ECT for cycloid psychosis. The secondary aim was to examine possible predictors of outcome. Methods: Data were obtained from the National Quality Register for ECT in Sweden. The study population was patients (n = 42) who received ECT for acute polymorphic psychotic disorder without symptoms of schizophrenia or for cycloid psychosis between 2011–2015 in 13 hospitals. Remission and response rates were calculated using Clinical Global Impression-Severity (CGI-S) and -Improvement scores, respectively. Variables with possible predictive value were tested using Chi-square and Fisher’s exact test. Results: The response rate was 90.5%. The remission rate was 45.2%. Of 42 patients, 40 improved their CGI-S score after ECT (p < 0.001). The mean number of ECT treatments was 2.5 for non-responders and 7.0 for responders (p = 0.010). The mean number of ECT treatments did not differ significantly between remitters and non-remitters (7.2 vs 6.1, p = 0.31). None of the other investigated potential predictors was statistically significantly associated with outcome. Conclusions: ECT is an effective treatment for cycloid psychosis. Future studies need to compare the outcome of ECT to that of other treatment strategies. Clinical implications: The high response rate with ECT indicates that cycloid psychosis is a clinically useful diagnosis.
Lipid Profile and Antioxidant Activity of Macadamia Nuts (Macadamia integrifolia) Cultivated in Venezuela

Macadamia nuts (Macadamia integrifolia) grown in Venezuela have showed an average total fat content of 70%. Oleic acid (18:1) was the main monounsaturated fatty acid (MUFA) (51.3%), followed by palmitoleic acid (16:1, 22.6%). The content of polyunsaturated fatty acids (PUFAs), C18:2 and C18:3 represented 5.4%. Thus, MUFAs and PUFAs together constituted more than 80% of the total fatty acids present. Trans-vaccenic acid was also present (3%). As regards to other phytochemical compounds, tocopherols and tocotrienols were not found in the sample, but the presence of squalene was detected. The antioxidant activity (44.2%) of the extract was produced by the phytochemicals present.
Gender Disparity between Cutaneous and Non-Cutaneous Manifestations of Lyme Borreliosis

Cutaneous manifestations of Lyme borreliosis in Europe include erythema migrans (EM) and acrodermatitis chronica atrophicans (ACA); the most common non-cutaneous manifestations are Lyme neuroborreliosis (LNB) and Lyme arthritis. The purpose of this study was to evaluate the gender distribution of patients with these clinical manifestations of Lyme borreliosis. Data on gender were obtained from the clinical records of patients with Lyme borreliosis aged ≥15 years who had been evaluated at the University Medical Center Ljubljana, Ljubljana, Slovenia. Among 10,539 patients diagnosed with EM, 6,245 (59.3%) were female and among 506 ACA patients 347 (68.6%) were female. In contrast, among the 60 patients with Lyme arthritis only 15 (25%) were female (p<0.0001 for the comparison of gender with EM or ACA) and among the 130 patients with LNB only 51 (39.2%) were females (p<0.0001for the comparison of gender with EM or ACA). Although the proportion that was female in the LNB group was greater than that of patients with Lyme arthritis, this difference did not reach statistical significance (p = 0.10). Although older individuals are more likely to be female in the general Slovenian population, the age of patients with cutaneous versus non-cutaneous manifestations was not the explanation for the observed differences in gender. In conclusion, patients with cutaneous manifestations of Lyme borreliosis were predominantly female, whereas those with non-cutaneous manifestations were predominantly male. This provocative finding is unexplained but may have direct relevance to the pathogenesis of Lyme borreliosis.
From Open Access to Open Data Markets: Increasing the Subtractability of Open Data

Much of earlier emphasis on open data as a public good has been focused primarily upon accessibility and has ruled out the role of rivalry in the creation of horizontal and vertical complements. Rather than framing open data as a public good, this paper positions open data as a common pool resource, which is subject to subtraction by commercial interests. Contrary to the prior depiction that the subtract ability of common pool resources is deleterious, we argue that subtraction is essential to attracting private investment. Specifically, making open data more subtract able, will not only attract further private and public use but also induce eventual releases of private and commercial data to form a marketplace of data complements. We further argue that most of the current open data initiatives should direct their attention towards the creation of a platform market to harness the distributed resources for creating digitalised innovation and services.
E-Commerce Product Recommendations by Analyzing Customer Personality

: Recommender systems attempt to highlight items that a target user is likely to find interesting. Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a live interaction. Collaborative filtering, the most successful recommender system technology to date, helps people make choices based on the opinions of other people. Recommender system is a topic which falls under the domain of information retrieval, data mining and machine learning. Recommender systems are widely used by famous websites like Amazon, Flip-Kart and many others. There are various types of recommender systems like collaborative filtering, content based filtering and hybrid recommender system. Recommender systems can be used for recommending various products like books, movies, music and any products in general. Various researchers until now have developed various algorithms to improve the accuracy of recommender systems and provide good quality recommendations. Algorithm and approach used determines the quality of recommendations.