Phase equilibria and phase transformations in the Ti-rich corner of the Fe-Ni-Ti system

While the main features of the Fe-Ni-Ti system are well known at low Ti content, literature review of the Ti-rich corner revealed inconsistencies between experimental reports. This investigation presents new experimental results, defined to remove the uncertainties concerning melting behavior and solid-state phase equilibria of the (Ni,Fe)Ti2 phase with the adjacent (Fe,Ni)Ti (B2, CsCl-type structure) and Beta-Ti (A2, W-type) phases. Six samples have been prepared and examined by differential thermal analysis performed in yttria and alumina crucibles, and by scanning electron microscopy in the as-cast state as well as equilibrated at 900°C

Skin acrometastases in squamous cell carcinoma of the tongue.

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First-principles equation of state and phase stability for the Ni-Al system under high pressures

The equation of state (EOS) of alloys at high pressures is generalized with the cluster expansion method. It is shown that this provides a more accurate description. The low temperature EOSs of Ni-Al alloys on FCC and BCC lattices are obtained with density functional calculations, and the results are in good agreement with experiments. The merits of the generalized EOS model are confirmed by comparison with the mixing model. In addition, the FCC phase diagram of the Ni-Al system is calculated by cluster variation method (CVM) with both spin-polarized and non-spin-polarized effective cluster interactions (ECI). The influence of magnetic energy on the phase stability is analyzed. A long-standing discrepancy between ab initio formation enthalpies and experimental data is addressed by defining a better reference state. This aids both evaluation of an ab initio phase diagram and understanding the thermodynamic behaviors of alloys and compounds. For the first time the high-pressure behavior of order-disorder transition is investigated by ab initio calculations. It is found that order-disorder temperatures follow the Simon melting equation. This may be instructive for experimental and theoretical research on the effect of an order-disorder transition on shock Hugoniots.Comment: 27 pages, 12 figure

Retinal Tectonics after Macular Pucker Surgery: Thickness Changes and en Face Displacement Recovery

Purpose: To study visual function, retinal layer thickness changes, and tangential displacement after pars plana vitrectomy for epiretinal membrane.Methods: Retrospective series of patients undergoing pars plana vitrectomy for epiretinal membrane, with 6-month follow-up including best-corrected visual acuity, optical coherence tomography, M-charts, epiretinal membrane grading, and infrared fundus photograph at time 0 (T0, preop) at months 1 (T1), 3 (T3), and 6 (T6) postop (+/- 1 week). Retinal layer thickness and tangential ( en face ) retinal displacement between successive times for the entire retinal surface and the central horizontal and vertical meridian were also measured. En face displacement was calculated as optical flow of consecutive images.Results: Average best-corrected visual acuity improved from 0.28 +/- 0.08 logarithm of Minimum Angle of Resolution at T0 to 0.16 +/- 0.25 at T6 ( P = 0.05), best-corrected visual acuity improvement correlated with best corrected visual acuity (BCVA) at T0 ( P < 0.001). Vertical metamorphopsia decreased from 1.33 degrees +/- 0.70 degrees at T0 to 0.82 degrees +/- 0.69 degrees at T6 ( P < 0.05). Foveal thickness reduced from 453 +/- 53 mu m at T0 to 359 +/- 31 mu m at T6 ( P < 0.05) and reduction correlated with best-corrected visual acuity improvement ( P < 0.05). Foveal layers decreased ( P < 0.05) in all cases. The mean en face deformation was 155.82 +/- 50.17 m and mostly occurred in the first month: T0-T1 displacement was 83.59 +/- 30.28 mu m, T1-T3 was 36.28 +/- 14.45 mu m, while T3-T6 was 39.11 +/- 22.79 mu m ( P < 0.001) on average. Perifoveal and parafoveal deformation correlated with optical coherence tomography foveal thickness reduction at all time intervals (1, 3, and 6 months: P < 0.01).Conclusion: Epiretinal membrane peeling affects all retinal layer thickness and results in new force balance across the entire retina and tangential displacement. Both en face and in-depth changes correlate with visual function

Could Small Neurotoxins-Peptides be Expressed during SARS-CoV-2 Infection?

SARS-CoV-2 pathogenesis has been recently extended to human central nervous system (CNS), in addition to nasopharyngeal truck, eye, lung and gut. The recent literature highlights that some SARS-CoV-2 spike glycoprotein regions homologous to neurotoxin-like peptides might bind to human nicotinic Acetyl-Choline Receptors (nAChRs). Spike-nAChR interaction can probably cause dysregulation of CNS and cholinergic anti-inflammatory pathways and uncontrolled im-mune-response, both associated to a severe COVID-19 pathophysiology. Herein, we hypothesize that inside the Open Reading Frame (ORF) region of spike glycoprotein, the RNA polymerase can translate small neurotoxic peptides by means of a “jumping mechanism” already demonstrated in other coronaviruses. These small peptides can bind the snAChRs instead of Spike glycoproteins. A striking homology occurred between these small peptides observed by sequence retrieval and pro-teins alignment. Acting as nAChRs antagonists, these small peptides (conotoxins) could be the ex-planation for the extrapulmonary clinical manifestations (neurological, hemorrhagic and thrombot-ic expressions, the prolonged apnea, the cardiocirculatory collapse, the heart arrhythmias, the ven-tricular tachycardia, the body temperature alteration, the electrolyte K+ imbalance and finally the significant reduction of butyryl cholinesterase (BuChE) plasma levels, as observed in COVID-19 patients. Several factors might induce the expression of these small peptides, including microbiota. The main hypothesis regarding the presence of these small peptides opens a new scenario on the eti-ology of COVID-19 clinical symptoms observed so far, including the neurological manifestations

Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form Games

We introduce a new approach for computing optimal equilibria and mechanisms via learning in games. It applies to extensive-form settings with any number of players, including mechanism design, information design, and solution concepts such as correlated, communication, and certification equilibria. We observe that optimal equilibria are minimax equilibrium strategies of a player in an extensive-form zero-sum game. This reformulation allows us to apply techniques for learning in zero-sum games, yielding the first learning dynamics that converge to optimal equilibria, not only in empirical averages, but also in iterates. We demonstrate the practical scalability and flexibility of our approach by attaining state-of-the-art performance in benchmark tabular games, and by computing an optimal mechanism for a sequential auction design problem using deep reinforcement learning

Artificial intelligence for renal cancer: From imaging to histology and beyond

Artificial intelligence (AI) has made considerable progress within the last decade and is the subject of contemporary literature. This trend is driven by improved computational abilities and increasing amounts of complex data that allow for new approaches in analysis and interpretation. Renal cell carcinoma (RCC) has a rising incidence since most tumors are now detected at an earlier stage due to improved imaging. This creates considerable challenges as approximately 10%–17% of kidney tumors are designated as benign in histopathological evaluation; however, certain co-morbid populations (the obese and elderly) have an increased peri-interventional risk. AI offers an alternative solution by helping to optimize precision and guidance for diagnostic and therapeutic decisions. The narrative review introduced basic principles and provide a comprehensive overview of current AI techniques for RCC. Currently, AI applications can be found in any aspect of RCC management including diagnostics, perioperative care, pathology, and follow-up. Most commonly applied models include neural networks, random forest, support vector machines, and regression. However, for implementation in daily practice, health care providers need to develop a basic understanding and establish interdisciplinary collaborations in order to standardize datasets, define meaningful endpoints, and unify interpretation

Collagenase clostridium histolyticum for the treatment of Peyronie's disease: a prospective Italian multicentric study

Peyronie's disease (PD) is a common condition which results in penile curvature making sexual intercourse difficult or impossible. Collagenase clostridium histolyticum (CCH) is the first licensed drug for the treatment of PD and is indicated in patients with palpable plaque and curvature deformity of at least 30° of curvature. However, only few monocentric studies are available in the current literature and this is the first national multicentric study focusing on this new treatment. In five Italian centres, 135 patients have completed the treatment with three injections of CCH using Ralph's shortened modified protocol. The protocol consisted of three intralesional injections of CCH (0.9 mg) given at 4-weekly intervals in addiction to a combination of home modelling, stretching and a vacuum device on a daily basis. An improvement in the angle of curvature was recorded in 128/135 patients (94.8%) by a mean (range) of 19.1 (0–40)° or 42.9 (0–67)% from baseline (p < 0.001). There was also a statistically significant improvement in all IIEF and PDQ questionnaires subdomains (p < 0.001 in all subdomains). This prospective multicentric study confirms that the three-injection protocol is effective enough to achieve a good result and to minimize the cost of the treatment