Miracle-dz/UniFAR-FTUs huggingface dataset:
L ’ utilité d ’ un questionnaire d ’ évaluation détaillée de la douleur modifié : les caractéristiques et l ’ état fonctionnel des patients à leur arrivée à une clinique

1Comprehensive Pain Program; 2University of Toronto Centre for the Study of Pain; 3Krembil Neuroscience Center, Toronto Western Hospital, Toronto, Ontario Correspondence: Dr Jennifer M Nelli, Comprehensive Pain Program, Toronto Western Hospital, 4F811, 399 Bathurst Street, Toronto, Ontario M5T 2S8. Telephone 416-209-6829 and 416-603-5380, fax 416-603-5725, e-mail jennifer.nelli@utoronto.ca With an increasing understanding of chronic pain as a complex biopsychosocial phenomenon, investigators and clinicians have attempted to assess chronic pain patients with multiple and often lengthy assessment tools. Although the use of these tools leads to a more comprehensive assessment, it may be cumbersome and time consuming, and many pain clinics do not have the resources for such assessment. The Comprehensive Pain Evaluation Questionnaire (CPEQ) (1) was designed as a brief inventory that could quickly and easily be applied in the setting of a chronic pain clinic. The CPEQ is modelled after the Multidimensional Pain Inventory (MPI) (2), one of the most commonly used measures of chronic pain (3). A vast amount of research concerning the classification of chronic pain patients has focused on the MPI as an assessment tool. In one such study, Turk and Rudy (4) reviewed 140 consecutive new patients referred to an outpatient pain clinic in Pittsburgh, Pennsylvania (USA), and presented an empirically derived pain patient taxonomy based on scores from the MPI, plus other measures. Using cluster analysis, Turk and Rudy identified three distinct profiles of pain patients. These patient profiles were labelled as ‘Dysfunctional’, ie, patients who reported relatively high original artiClE
A Game of Dice: Machine Learning and the Question Concerning Art

We review some practical and philosophical questions raised by the use of machine learning in creative practice. Beyond the obvious problems regarding plagiarism and authorship, we argue that the novelty in AI Art relies mostly on a narrow machine learning contribution : manifold approximation. Nevertheless, this contribution creates a radical shift in the way we have to consider this movement. Is this omnipotent tool a blessing or a curse for the artists?
Spreading Patterns of Malicious Information on Single‐Lane Platooned Traffic in a Connected Environment

The connected vehicle can be easily attacked by cyber threats due to its communication through the wireless network in an open‐access environment. But very few studies have paid attention to the spreading of malicious information such as denial of service, message delay/replay, and eavesdropping generated by cyberattacks. To this end, this article introduces an analytical model, named vehicular malicious information propagation (VMIP), which integrates a classical epidemic model through two‐layer system structure, in which the upper layer describes the malicious information spreading and the lower describes the traffic flow dynamics. The proposed VMIP model is designated for platooned (one‐lane, particularly) traffic. Numerical experiments show the proposed model can efficiently describe the interactions between traffic dynamics and malicious information spreading; and the information propagation highly depends on traffic flow patterns. This article is expected to contribute to a better understanding of the impacts of cyberattacks on traffic and lays a foundation for future development of control strategies on mitigating the disastrous effects of cyberattacks.
LEAN BEHAVIOR IMPACT TOWARDS LEAN MANAGEMENT: A CASE STUDY

Lean behavior is an essential element to create a continuous improvement culture in the service organization. Meanwhile, continuous improvement is defined as the never-ending efforts for improvement involving everyone in organization. The purpose of this study is to evaluate the changes of behavior practices after the introduction of lean tools and to discuss on how lean behavior in developing the continuous improvement culture in an office environment. This study focuses on self-administered questionnaire method to obtain the real time data for the analysis of behavior practices. Ford Questionnaire is used and distributed to the employees of different management levels in Business Development and IT department. The obtained results are analyzed using the Statistical Package for the Social Sciences (SPSS) software. The same questionnaire survey is conducted after the introduction of lean tools. The expected outcomes of this study is to determine the level of lean behavior practices in the office department and to provide a clear understanding on some lean behavior practices that need to be nurtured among the employees in order to produce a healthy work environment.
Stochastic analysis and invariant subspace method for handling option pricing with numerical simulation

‎ In this paper option pricing is given via stochastic analysis and invariant subspace method. Finally numerical solutions is driven and shown via diagram. The considered model is one of the most well known non-linear time series model in which the switching mechanism is controlled by an unobservable state variable that follows a first-order Markov chain. Some analytical solutions for option pricing are given under our considered model. Then numerical solutions are presented via finite difference method.
Active Working Memory and Simple Cognitive Operations

Abstract Working memory is thought to serve as a buffer for ongoing cognitive operations, even in tasks that have no obvious memory requirements. This conceptualization has been supported by dual-task experiments, in which interference is observed between a primary task involving short-term memory storage and a secondary task that presumably requires the same buffer as the primary task. Little or no interference is typically observed when the secondary task is very simple. Here, we test the hypothesis that even very simple tasks require the working memory buffer, but interference can be minimized by using activity-silent representations to store the information from the primary task. We tested this hypothesis using dual-task paradigm in which a simple discrimination task was interposed in the retention interval of a change detection task. We used contralateral delay activity (CDA) to track the active maintenance of information for the change detection task. We found that the CDA was massively disrupted after the interposed task. Despite this disruption of active maintenance, we found that performance in the change detection task was only slightly impaired, suggesting that activity-silent representations were used to retain the information for the change detection task. A second experiment replicated this result and also showed that automated discriminations could be performed without producing a large CDA disruption. Together, these results suggest that simple but non-automated discrimination tasks require the same processes that underlie active maintenance of information in working memory.
Radar clutter as an indicator for vegetation classification using a single dual polarimetric TSX-1 image

This paper investigates the ability to classify different vegetation types covering a semi-arid Mediterranean vegetated area using single-polarization SAR images from the TerraSAR-X (TSX-1) satellite. Based on statistical moments such as mean, standard deviation (STDEV), skewness and kurtosis, we found textural differences useful for the classification of the vegetation types. The research site, located near Zafit Hill, Israel, includes several different vegetation types such as pines and cypress forests with shrubs as an underlying vegetation layer (understory), olive orchards, eucalyptus clusters, natural grove areas with the presence of stones and smooth rocks, a wet cotton field, and smooth agricultural fields after harvest. In each vegetation type area, 40 equal polygons (10*10 pixels each) were identified on an optical image and defined on the TSX-1 image; 280 polygons in total were identified. The aforementioned statistical parameters were produced for each polygon, and co-variance matrices of combinations of two, three, or all four parameters together were produced. It was found that using the Mahalanobis distance of the mean-STDEV-skewness combination after applying a mode filter (5*5 in size) was the best way to classify the vegetation types in the research area.
The Mass–Metallicity Relation of Local Active Galaxies

We systematically measure the gas-phase metallicities and the mass–metallicity relation of a large sample of local active galaxies for the first time. Observed emission-line fluxes from the Sloan Digital Sky Survey are compared to a four-dimensional grid of photoionization models using the Bayesian parameter estimation code NebulaBayes. For the first time we take into account arbitrary mixing between H ii region and narrow-line region (NLR) emission, and the models are also varied with metallicity, ionization parameter in the NLR, and gas pressure. The active galactic nucleus oxygen abundance is found to increase by Δ O / H ∼ 0.1 dex as a function of host galaxy stellar mass over the range 10.1 < log M * / M ⊙ < 11.3 . We also measure the metallicity and ionization parameter of 231,000 star-forming galaxies for comparison with the sample of 7670 Seyfert 2 galaxies. A systematic offset in oxygen abundance of 0.09 dex is observed between the mass–metallicity relations of the star-forming and active galaxies. We investigate potential causes of the offset, including sample selection and the treatment in the models of diffuse ionized gas, pressure, and ionization parameter. We cannot identify the major cause(s), but suspect contributions due to deficiencies in modeling the ionizing spectra and the treatment of dust physics. Optical diagnostic diagrams are presented with the star-forming and Seyfert data colored by the inferred oxygen abundance, ionization parameter, and gas pressure, clearly illustrating the trends in these quantities.
Tunable auto-combustion preparation of TiO2 nanostructures as efficient adsorbents for the removal of an anionic textile dye

We have developed a new route for the synthesis of pure TiO2 nanostructures via a facile auto-combustion method followed by heat treatment. We have tuned the produced phases, morphologies, and crystallite sizes of the nano-sized TiO2 products through an auto-combustion method employing different fuels and various fuel-to-oxidant equivalence ratios, Φc. The as-synthesized products were analyzed by means of FE-SEM, FT-IR, XRD, TEM, BET, and thermal analyses. Interestingly, urea fuel at Φc = 1 generated a pure anatase TiO2 phase (U1) having almost the smallest crystallite size (11.9 nm) and the highest adsorption capacity (135 mg g−1) for the removal of Reactive Red 195 (RR195) dye from aqueous solutions. Moreover, the adsorption data could be described well using the pseudo-second-order kinetic and Langmuir isotherm models. Based on the calculated thermodynamic parameters: ΔH0 (1.343 kJ mol−1), ΔG0 (from −4.630 to −5.031 kJ mol−1), and Ea (18.46 kJ mol−1), the adsorption of RR195 dye on the as-prepared TiO2 nano-adsorbent is an endothermic, spontaneous, and physisorption process, respectively. Moreover, the as-prepared TiO2 adsorbent is a promising candidate for the removal of RR195 textile dye from aqueous media based on its reusability, high stability, and high adsorption capacity.
A Systematic Study of Superluminous Supernova Light-curve Models Using Clustering

Superluminous supernova (SLSN) light curves exhibit superior diversity compared to their regular-luminosity counterparts in terms of rise and decline timescales, peak luminosities, and overall shapes. It remains unclear whether this striking variety arises due to a dominant power input mechanism involving many underlying parameters or due to contributions by different progenitor channels. In this work, we propose that a systematic quantitative study of SLSN light-curve timescales and shape properties, such as symmetry around peak luminosity, can be used to characterize these enthralling stellar explosions. We find that applying clustering analysis to the properties of model SLSN light curves, powered by either a magnetar spindown or a supernova ejecta–circumstellar matter interaction mechanism, can yield a distinction between the two, especially in terms of light-curve symmetry. We show that most events in the observed SLSN sample with well-constrained light curves and early detections are strongly associated with clusters dominated by circumstellar interaction models. Magnetar spindown models also show association at a lower degree but have difficulty in reproducing fast evolving and fully symmetric light curves. We believe this is due to the truncated nature of the circumstellar interaction shock energy input compared to decreasing but continuous power input sources like magnetar spindown and radioactive 56Ni decay. Our study demonstrates the importance of clustering analysis in characterizing SLSNe based on high-cadence photometric observations that will be made available in the near future by surveys like the Large Synoptic Survey Telescope, Zwicky Transient Facility, and Panoramic Survey Telescope and Rapid Response System.
Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm

Abstract. Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO2 (XCO2) for the roughly 100 000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25 %, is required in order to accurately infer carbon sources and sinks from XCO2, significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20 % over land and 40 % over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO2 data record continues to expand.
Chemosensitizing effects of methyl jasmonate on paclitaxel-resistant androgen-dependent and independent prostate cancer cell lines

The taxane-based therapy provides survival benefit in patients with metastatic prostate cancer; however, the average survival is less than 20 months due to the partial taxane-related chemoresistance. Innovative strategies are needed to overcome the chemoresistance for improved patient survival. In this project, paclitaxel-resistance was developed on androgen-independent PC3 and androgen-dependent 22Rv1 and LNCaP human prostate cancer (PCa) cell lines to investigate the efficacy of methyl jasmonate (MeJa), an anti-cancer drug, in overcoming the chemoresistance. The PCa cell lines were maintained in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS) at 37? C under 5% CO2. The cell lines were exposed to the gradually increasing doses of paclitaxel. Since the resistance on LNCaP could not be achieved, the study was continued with 22Rv1 cell line. It was demonstrated that paclitaxel-resistant cell lines overexpress ABCB1. Resistance levels of cells and MeJa activity in all resistant and parental lines were measured using CellTiter-Glo? luminescent assay. Test results were compared with Student? s t-test or analysis of variance (ANOVA). P? 0.05 (two-tailed) was considered to be significant. In conclusion, MeJa showed more cytotoxicity on paclitaxel resistant PC3 (PC3-PtxR) cells than resistant 22Rv1 (22Rv1-PtxR) cells. Detection of cytotoxic effects of MeJa in overcoming paclitaxel resistance may contribute to the development of alternative new compounds for the prevention or chemosensitization of resistance to chemotherapeutics such as paclitaxel.
Towards Human Body-Part Learning for Model-Free Gait Recognition

Gait based biometric aims to discriminate among people by the way or manner they walk. It represents a biometric at distance which has many advantages over other biometric modalities. State-of-the-art methods require a limited cooperation from the individuals. Consequently, contrary to other modalities, gait is a non-invasive approach. As a behavioral analysis, gait is difficult to circumvent. Moreover, gait can be performed without the subject being aware of it. Consequently, it is more difficult to try to tamper one own biometric signature. In this paper we review different features and approaches used in gait recognition. A novel method able to learn the discriminative human body-parts to improve the recognition accuracy will be introduced. Extensive experiments will be performed on CASIA gait benchmark database and results will be compared to state-of-the-art methods.
DECOMPOSABLE SEC-DED CODES OF ENHANCED AUGMENTED PRODUCT CODE CONSTRUCTION

Enhanced augmented product code construction (EAPCC) and its decomposable SEC-DED (singleerror-correcting/double-error-detecting) codes, which are composed by augmenting the simple component codes (2,1,2) and (2,1,1) on to a two dimensional general product code structure, are presented by this paper. Some of the best-known codes with minimum distance four that have been attained using this method have also been presented as a result of simulations.
BMO martingale method for backward stochastic differential equations driven by general càdlàg local martingales

In this paper we study time-discontinuous nonlinear multi-dimen-sional backward stochastic diﬀerential equations (BSDEs) driven by general c`adl`ag local martingales. The Lipschitz coeﬃcients of the generators are allowed to be unbounded. The time-discontin-uous BMO martingale theory, in particular Feﬀerman’s inequality, is used to study the existence and uniqueness of solution in S p with p ∈ (1 , ∞ ].
Response to Ranibizumab Following Tachyphylaxis to Bevacizumab in a Patient With Radiation Maculopathy Following Stereotactic Fractionated Radiotherapy for Optic Nerve Meningioma

Comment. Cysticercosis is the most common ocular parasitic infection in humans, caused by the larvae of the tapeworm Taenia solium. Humans and pigs act as the intermediate host by ingesting eggs or gravid proglottids (body segments). Once the eggs are ingested, oncospheres (larvae inside the egg that each have a ring of 6 hooks) are liberated. The oncospheres penetrate the intestinal wall, enter into portal vessels or the mesentric lymphatic system, and finally reach the systemic circulation. They are filtered out into the muscular tissues where they ultimately settle down and develop into the cyticerci (the resting stage of larva). Besides striated muscle, cysticerci may be seen in the eye and brain. The life cycle of the parasite is completed when humans ingest undercooked pork containing the cysticerci. In the human intestines, the cysts evaginate, and the scolex (head) anchors to the gut wall by means of its suckers and develops into an adult worm by gradual strobilization (the process of producing or growing new proglottids by asexual reproduction). The adult tapeworm resides in the small intestines for many years, and the only extraintestinal manifestation reported previously was in the spinal cord. In the present series, we report juvenile strobilate tapeworm presenting as fibrinous uveitis in 2 patients. Fibrinous anterior uveitis has been reported in cysticercosis cellulose infections. In the present series, the 48-year-old man living in the Himalayan foothills of North India (case 1) had severe fibrinous uveitis with an abscess in the anterior chamber. There was no cyst seen clinically. A histopathologic examination of the iridectomy specimen showed the abscess wall attached to the iris. Because there were no parts of the tapeworm seen attached to the wall, it was reported as an abscess wall. However, because the eye subsequently developed phthisis bulbi, it is possible that there was a cyst in the eye that ruptured, causing severe inflammation and evagination of the juvenile worm. For the 38year-old man living in Nepal (case 2), we performed a pars plana vitrectomy, and the subretinal cyst was removed in toto. However, this patient had severe postoperative fibrinous uveitis and was subsequently found to be harboring a juvenile tapeworm in the anterior chamber. In this case, there could possibly have been another small cyst/larva present behind the iris or in the angle of the anterior chamber that was missed initially and that later evolved into a juvenile worm in the anterior chamber. Just how the adult tapeworm can survive in theanteriorchamber isunclear. The best postulate is that the fluid-filledcystofascolexrupturesand that the evaginated scolex then attaches with hooks to the iris (like the intestinal wall) and grows thereafter.