Epoxy/ graphene nanocomposites – processing and properties: a review

Graphene has recently attracted significant academic and industrial interest because of its excellent performance in mechanical, electrical and thermal applications. Graphene can significantly improve physical properties of epoxy at extremely small loading when incorporated appropriately. Herein, the structure, preparation and properties of epoxy/graphene nanocomposites are reviewed in general, along with detailed examples drawn from the key scientific literature. The modification of graphene and the utilization of these materials in the fabrication of nanocomposites with different processing methods have been explored. This review has been focused on the processing methods and mechanical, electrical, thermal, and fire retardant properties of the nanocomposites. The synergic effects of graphene and other fillers in epoxy matrix have been summarised as well

Optimisation of deep drawn corners subject to hot stamping constraints using a novel deep-learning-based platform

State-of-the-art hot stamping processes offer improved material formability and therefore have potential to successfully form challenging components. The feasibility of components to be formed through these processes is dependent on their geometric design and its complex interactions with the hot stamping environment. In industrial practice, trial-and-error approaches are currently used to update non-feasible designs where simulation runs are needed each time a design change is made. These approaches make the design process resource intensive and require considerable numerical and process expertise. To demonstrate a superior approach, this study presents a novel application of a deep-learning-based optimisation platform which adopts a non-parametric geometric modelling strategy. Here, deep drawn corner geometries from different geometry subclasses were optimised to minimise wasted volume due to radii while avoiding excessive post-stamping thinning. A neural network was trained to generate families of deep drawn corner geometries where each geometry was conditioned on an input latent vector. Another neural network was trained to predict the thinning distributions obtained from forming these geometries through a hot stamping process. Guided by these distributions, the latent vector, and therefore geometry, was iteratively updated by a new gradient-based optimisation technique. Overall, it is demonstrated that the platform is capable of optimising geometries, irrespective of complexity, subject to imposed post-stamped thinning constraints

Orthotopic liver transplantation in U.S. veterans under primary tacrolimus immunosupression.

The evolution and refinement of surgical techniques, per ioperative patient care, and immunosuppression hav~ estab~ished orthoto~ic li~er transplantation (OLTX) as a ~ighly successful therapeutic modality for patients wrth end-stage hver disease. In February 1989,Tacrohmus (Prograf®, formerly FK 506)was first used successfully at the University of Pittsburgh Medical Center to treat patients with rejection refractory to cyclosporine-based immunosuppression." Clinical trials utilizing Tacrolimus in solid organ transplantation followed, and in April of 1994 it was approved for use by the Food and Drug Administration

Early death or retransplantation in adults after orthotopic liver transplantation: Can outcome be predicted?

Early, reliable outcome prediction after a liver transplant would help improve organ use by minimizing unnecessary retransplantations. At the same time, early intervention in those cases destined to fail may ameliorate the high morbidity and mortality associated with retransplantation. The purpose of this study was to analyze several parameters that have been identified in the past as being associated with patient and graft outcome, and to try to develop a model that would allow us to make predictions based on data available in the early postoperative period. A total of 148 patients were followed in a prospective, observational study. Graft failure was defined as patient death or retransplantation within 3 months of surgery. Preoperative variables studied included patient demographics, need for life support, presence of ascites, serum bilirubin, serum albumin, prothrombin time, serum creatinine, and the results of the cytotoxic crossmatch. During the first 5 postoperative days, standard measurements included serum transaminases, serum bilirubin, ketone body ratio, prothrombin time, factor V, and serum lactate. Oxygen consumption was measured shortly after surgery, once the patients had rewarmed to 36°C. There were 131 successful transplants (88.5%) and 17 failures (11.5%). Most of the variables studied were found to be associated with outcome (by univariate analysis) at different points in the early postoperative period. However, receiver operating characteristic curve analysis showed that the predictive ability of even the best parameter was not adequate to make decisions on individual patients. Multivariate analysis, using stepwise logistic regression, yielded a model with an overall accuracy of 92.7%. Again, receiver operating characteristic curve analysis suggested that this model did not achieve the discriminating power needed for routine clinical use. We are still not able to accurately predict outcome in the early posttransplant period. We must be very careful when evaluating parameters, or scoring systems, that are said to accomplish this. It is especially important in this era of cost containment, with its renewed pressures to guide therapy based on our perceived understanding of a patient’s future clinical course. © 1994 by Williams & Wilkins

Revisiting the assessment of tremor: clinical review

Tremor, an involuntary, rhythmic, and oscillatory movement of a body part, is a frequent presenting symptom to general practice and by far the most common movement disorder presentation, impacting up to 15% of such cases.1 A common initial pattern is symmetric upper-limb involvement during posture and action. Although patients are often worried about Parkinson’s disease (PD), PD tremor usually has easily recognisable features.2 This concern tends to lead to frequent referrals for specialist input despite an alternative diagnosis being more likely in a majority of cases. Essential tremor (ET) is the most common diagnosis given to patients with this presentation, which is estimated to affect 0.4–6.0% of the general population.3 This may be an overestimate as the rubric of ET and the relationship between clinical features and underlying pathophysiology is uncertain. These aspects also potentially contribute to variable diagnostic and treatment outcomes.4 A recent Movement Disorder Society consensus on phenotyping charts a course towards more precise classification.5 This will not only be useful for research but also help in clarifying common clinical syndromes seen in everyday practice. This article outlines an approach to upper-limb tremor presentations in adult patients, developing a previously proposed three cardinal question method for neck pain6 while highlighting salient aspects of the consensus statement that could potentially aid in clinical stratification of cases

Тонзилектомия − съвременни оперативни техники

Целта на настоящата статия е да се направи сравнително клинично изследване на съвременните оперативни техники и конвенционалната тонзилектомия. За период от две години в УНГ-клиниката на ВМА – София бяха извършени 176 тонзилектомии на болни на възраст от 10 до 45 години. От тях 45% бяха оперирани конвенционално, при 35% бе използван ултразвуков хармоничен скалпел Ultracision, а при останалите 20% бе използван радиочестотен апарат Coblator.Резултатите показаха чувствителна разлика в полза на съвременните оперативни техники (утразвуковата методика и коблатор-техниката).------------------------------------- The purpose of the current article is to make a comparative clinical study of modern operating techniques and cold dissection tonsillectomy. During a period of two years in the ENT department at the Military Medical Academy - Sofia were performed 176 tonsillectomies in patiens between 10 and 45 years of age. 45% of the patients were operated using the conventional methods, 35% were operated using Ultracision and 20% were operated using the radiofrequency Coblation technology.The results showed considerable difference in favor of moden operating techniques (ultrasonic scalpel tonsillectomy or coblation tonsillectomy)

Analysis of a Mathematical Model in a Food Web System Containing Scavenger Species

في هذا البحث قد تم رياضيا صياغة ديناميكية أنواع صائد الفرائس في نموذج شبكة الغذاء بدمج التأخير الزمني و حصاد الفريسة. ان حدود جميع حلول النموذج قد تم تنفيذها. تمت مناقشة الوجود وكذلك تحليل الأستقرار لجميع احتمالات نقاط الأتزان الموجبة. كذلك في ظل تأخير زمني معين أثبتنا أن نموذجنا. قد أظهر تشعب هوبف دون الحرج. وعلاوة على ذلك فاننا قد درسنا المحاكاة العددية للنموذج لتأكيد اكتشافنا التحليلي.In this paper, the dynamics of scavenger species  in a web food model  incorporating time delay and  prey harvesting  is formulated mathematically. Boundednes of all  solutions of the model carried out. The existence as well as stability analysis of all possible positive equilibrium points are discussed. Also, we proved that under certain time delay, our model exhibits a subcritical Hopfbifurcation. Furthermore, to confirm our analytical finding, we studied numerical simulation for the model

Deformation and thinning field prediction for HFQ® formed panel components using convolutional neural networks

The novel Hot Forming and cold die Quenching (HFQ®) process can provide cost-effective and complex deep drawn solutions through high strength aluminium alloys. However, the unfamiliarity of the new process prevents its widescale adoption in industrial settings, while accurate Finite Element (FE) simulations using the most advanced material models take place late in design processes and require forming process expertise. Machine learning technologies have recently been proven successful in learning complex system behaviour from representative examples and have the potential to be used as design support tools for new forming technologies such as HFQ®. This study, for the first time, presents a novel application of a Convolutional Neural Network (CNN) based surrogate to predict the deformation and thinning fields for variable deep drawn geometries formed using HFQ® technology. A dataset based on deep drawn geometries and corresponding FE results is generated and used to train the model. The results show that near indistinguishable full field predictions in real time are obtained from the surrogate when compared with HFQ® simulations. This technique can be adopted in industrial settings to aid in both concept and detailed component design for complex-shaped panel components formed under HFQ® conditions, without underlying knowledge of the forming process

Neglected Tropical Diseases. The Place of Ivermectin in the Elimination Programs

The World Health Organization identifies as neglected nineteen tropical diseases with bacterial, viral and parasitic etiology, of which two are ophthalmological. These diseases affect over one billion people worldwide, especially communities in developing countries, with limited access to healthcare, clean water, and sewerage. These include: trachoma, onchocerciasis (river blindness), leprosy, leishmaniasis, schistosomiasis, foodborne trematode infections, dracunculiasis, Chagas disease, Human African trypanosomiasis, lymphatic filariasis (elephantiasis), cysticercosis, echinococcosis, soil-transmitted helminthiases, Dengue, rabies, yaws, scabies, Buruli ulcer, mycetoma, chromoblastomycosis and other deep mycoses. The global effort in fighting neglected tropical diseases is one of the biggest initiatives in the field of public health. On the 28th of January 2021 the World Health Organization initiated a new ten-year plan for the eradication of neglected tropical diseases. It aims to lower the mortality, new disability cases and suffering of more than one billion people