45 research outputs found

    EMPIRIJSKA STUDIJA IMPLIKACIJA KVALITATIVNIH FAKTORA U DONOŠENJU ODLUKA VEZANIH ZA RAZINU MATERIJALNOSTI. SLUČAJ RUMUNJSKE

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    The paper aims to present the importance of qualitative factors in determining the materiality level in an audit mission. According to the literature a quantitative approach of materiality is insufficient for appropriate decisions, therefore it is required a more serious treatment of this issue. Data collected in the research were processed using the Ordered Logit Model, and the results showed that there is a significant correlation between the materiality level and the sectors in which the audited companies operate, the auditor’s experience in the field and the longevity of the relationship with the client. There is no any correlation between the materiality level and the needs of the users of financial statements or the management objectives.Rad želi predstaviti važnost kvalitativnih faktora u određivanju razine materijalnosti u postupku revizije. Literatura nam govori da kvantitativni pristup materijalnosti nije dovoljan za prikladne odluke, te je stoga potreban ozbiljniji pristup ovoj temi. Podaci sakupljeni u istraživanju obrađeni su pomoću Order Logit Modela a rezultati su pokazali da postoji značajna korelacija između razine materijalnosti i sektora u kojima djeluju revidirane tvrtke, revizorovo iskustvo na polju dugovječnosti odnosa s klijentom. Ne postoji nikakva korelacija između razine materijalnosti i potreba korisnika financijskih izvještaja ili ciljeva menadžmenta

    Evolution of the differential transverse momentum correlation function with centrality in Au+Au collisions at sNN=200\sqrt{s_{NN}} = 200 GeV

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    We present first measurements of the evolution of the differential transverse momentum correlation function, {\it C}, with collision centrality in Au+Au interactions at sNN=200\sqrt{s_{NN}} = 200 GeV. {\it C} exhibits a strong dependence on collision centrality that is qualitatively similar to that of number correlations previously reported. We use the observed longitudinal broadening of the near-side peak of {\it C} with increasing centrality to estimate the ratio of the shear viscosity to entropy density, η/s\eta/s, of the matter formed in central Au+Au interactions. We obtain an upper limit estimate of η/s\eta/s that suggests that the produced medium has a small viscosity per unit entropy.Comment: 7 pages, 4 figures, STAR paper published in Phys. Lett.

    Experimental and Theoretical Challenges in the Search for the Quark Gluon Plasma: The STAR Collaboration's Critical Assessment of the Evidence from RHIC Collisions

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    We review the most important experimental results from the first three years of nucleus-nucleus collision studies at RHIC, with emphasis on results from the STAR experiment, and we assess their interpretation and comparison to theory. The theory-experiment comparison suggests that central Au+Au collisions at RHIC produce dense, rapidly thermalizing matter characterized by: (1) initial energy densities above the critical values predicted by lattice QCD for establishment of a Quark-Gluon Plasma (QGP); (2) nearly ideal fluid flow, marked by constituent interactions of very short mean free path, established most probably at a stage preceding hadron formation; and (3) opacity to jets. Many of the observations are consistent with models incorporating QGP formation in the early collision stages, and have not found ready explanation in a hadronic framework. However, the measurements themselves do not yet establish unequivocal evidence for a transition to this new form of matter. The theoretical treatment of the collision evolution, despite impressive successes, invokes a suite of distinct models, degrees of freedom and assumptions of as yet unknown quantitative consequence. We pose a set of important open questions, and suggest additional measurements, at least some of which should be addressed in order to establish a compelling basis to conclude definitively that thermalized, deconfined quark-gluon matter has been produced at RHIC.Comment: 101 pages, 37 figures; revised version to Nucl. Phys.

    Hadronization geometry from net-charge angular correlations on momentum subspace (η,ϕ\eta,\phi) in Au-Au collisions at sNN=130\sqrt{s_{NN}} = 130 GeV

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    We present the first measurements of charge-dependent correlations on angular difference variables η1η2\eta_1 - \eta_2 (pseudorapidity) and ϕ1ϕ2\phi_1 - \phi_2 (azimuth) for primary charged hadrons with transverse momentum 0.15pt20.15 \leq p_t \leq 2 GeV/cc and η1.3|\eta| \leq 1.3 from Au-Au collisions at sNN=130\sqrt{s_{NN}} = 130 GeV. We observe correlation structures not predicted by theory but consistent with evolution of hadron emission geometry with increasing centrality from one-dimensional fragmentation of color strings along the beam direction to an at least two-dimensional hadronization geometry along the beam and azimuth directions of a hadron-opaque bulk medium.Comment: 8 pages, 4 figure

    Underlying Event measurements in pp collisions at s=0.9 \sqrt {s} = 0.9 and 7 TeV with the ALICE experiment at the LHC

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    AN ANALYSIS OF THE MANUFACTURING POSSIBILITY OF SPECIAL ANKLE FOOT ORTHOSIS COMPONENTS BY OMPARISON BETWEEN THE REQUIRED PRECISION AND THE VAILABLE PRECISION ON A VERTICAL MACHINING CENTER PROGRAMED WITH TOPSOLID

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    Validation of different solutions adopted to achieve new ankle foot orthosis involves among others their prototyping. In these paper we developed a representative part for two axis machining that requires the use of the main features of TopSolid Cad and Cam modules, and that assumes the use of the main manufacturing processes that usually may be met on a vertical machining center. Also, in order to determine the dimensional and geometrical deviations of the part this was done on the YMC 1050 machining center. After comparing the measured deviations with the requirements of various components of orthesis, we concluded that the available precision meets the requirements and that the machining center with TopSolid software that we have will enable us to realize special ankle foot orthosis of quality, for experimental research

    Comprehensive Review on the Use of Artificial Intelligence in Ophthalmology and Future Research Directions

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    Background: Having several applications in medicine, and in ophthalmology in particular, artificial intelligence (AI) tools have been used to detect visual function deficits, thus playing a key role in diagnosing eye diseases and in predicting the evolution of these common and disabling diseases. AI tools, i.e., artificial neural networks (ANNs), are progressively involved in detecting and customized control of ophthalmic diseases. The studies that refer to the efficiency of AI in medicine and especially in ophthalmology were analyzed in this review. Materials and Methods: We conducted a comprehensive review in order to collect all accounts published between 2015 and 2022 that refer to these applications of AI in medicine and especially in ophthalmology. Neural networks have a major role in establishing the demand to initiate preliminary anti-glaucoma therapy to stop the advance of the disease. Results: Different surveys in the literature review show the remarkable benefit of these AI tools in ophthalmology in evaluating the visual field, optic nerve, and retinal nerve fiber layer, thus ensuring a higher precision in detecting advances in glaucoma and retinal shifts in diabetes. We thus identified 1762 applications of artificial intelligence in ophthalmology: review articles and research articles (301 pub med, 144 scopus, 445 web of science, 872 science direct). Of these, we analyzed 70 articles and review papers (diabetic retinopathy (N = 24), glaucoma (N = 24), DMLV (N = 15), other pathologies (N = 7)) after applying the inclusion and exclusion criteria. Conclusion: In medicine, AI tools are used in surgery, radiology, gynecology, oncology, etc., in making a diagnosis, predicting the evolution of a disease, and assessing the prognosis in patients with oncological pathologies. In ophthalmology, AI potentially increases the patient’s access to screening/clinical diagnosis and decreases healthcare costs, mainly when there is a high risk of disease or communities face financial shortages. AI/DL (deep learning) algorithms using both OCT and FO images will change image analysis techniques and methodologies. Optimizing these (combined) technologies will accelerate progress in this area
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