Applying Free Microvascular Latissimus Dorsi Flaps for Reconstruction of Post-Ablative Defects Affecting the Skull Base

Introduction: Tumors of the head and neck area are complex and pose a significant challenge for radical resection and subsequent reconstruction especially when the skull base is affected. With evolution in surgical reconstructive techniques, better reconstruction of these complex post-ablative defects is now possible and facilitates more aggressive surgical management. The aim of this study was to investigate the course of reconstructive treatment and outcomes with use of free microvascular latissimus dorsi flaps after tumor ablation of skull base penetrating malignancies.Material and methods: All extensive skull base tumor resections with latissimus dorsi free flap reconstruction made in the General University hospital Gregorio Marañón, between January 2010 and December 2012 were reviewed.Results: Three different types of free latissimus dorsi flaps were used being the grafted muscle flap the most common one. Complications occurred in 44.4 % of patients but no flaps were lost. Two latissimus dorsi donor site seromas were observed (22.2%).Conclusion: For the reconstruction aim of extensive skull base defects, the latissimus dorsi free flap seems to be a reliable option

Demographic Determinants And Challenges To Social Protection For Maternity In Bulgaria

The starting point of this study is the understanding of maternity as a condition related to the biological and social function of women for the reproduction of human race, performed by the mother with the birth and upbringing of children in early childhood and to acquire the ability for economically independent living alone or together - in the family or the parents’ household. Placed on this basis, the issue of social protection in maternity becomes extremely relevant in the context of demographic and socio-economic challenges to the development of modern society. The study attempts to substantiate the thesis that the system of social payments for pregnancy, childbirth and child-rearing has unused potential to become a working tool of demographic policy with a significant contribution to improving the demographic profile of the Bulgarian population, in connection with which ideas are presented about the possibilities for their organisational development and improvement

Quantum computational chemistry methods for early-stage quantum computers

One of the first practical applications of quantum computers is expected to be molecular modelling. Performing this task would profoundly affect areas such as chemistry, materials science and drug synthesis. Modelling of molecules, which are classically intractable, can be achieved with just over $30$ qubits, whereas state of the art quantum computers already have more than $50$ qubits. The Variational Quantum Eigensolver (VQE) algorithm and VQE based protocols, are promising candidates to enable this task on emerging Noisy Intermediate-Scale Quantum (NISQ) computers. These protocols require short quantum circuits and short coherence times, and are particularly resilient to quantum errors. Nevertheless, there is still a significant gap between the accuracy and the coherence times of current NISQ computers, and the hardware requirements of VQE protocols to simulate practically interesting molecules. In this thesis, I present my contribution to narrowing this gap by developing VQE protocols for molecular modelling that are less demanding on quantum hardware. The VQE relies on the Rayleigh-Ritz variational principle to estimate the eigenvalues of a Hamiltonian operator, by minimizing its expectation value with respect to a trial quantum state, prepared by an ansatz. A major challenge for the practical realisation of VQE protocols on NISQ computers is to construct an ansatz that: (1) can accurately approximate the eigenstates of the Hamiltonian; (2) is easy to optimize; and (3) can be implemented by a shallow circuit, within the capabilities of a NISQ computer. The most widely used, unitary coupled cluster (UCC), type of ans\"atze mathematically correspond to a product of unitary evolutions of fermionic excitation operators. Owing to their fermionic structure, UCC ans\"atze preserve the symmetries of electronic wavefunctions, and thus are accurate and easy to optimize. Nevertheless, UCC ans\"atze are implemented by high depth circuits, which severely limit the size of the molecules that can be reliably simulated on NISQ computers. In this thesis, I begin by constructing efficient quantum circuits to perform evolutions of fermionic excitation operators. The circuits are optimized in the number of two-qubit entangling gates, which are the current bottleneck of NISQ computers. Compared to the standard circuits used to implement evolutions of fermionic excitation operators, the circuits derived in this thesis reduce the number of two-qubit entangling gates by more than $70\%$ on average. As an intermediate result, I also derive efficient circuits to perform evolutions of qubit excitation operators (excitation operators that account for qubit, rather than fermionic commutation relations). Even with the fermionic-excitation-evolution circuits derived here, UCC ans\"atze still require very long circuits, with a particularly large number of two-qubit entangling gates. In this thesis, I consider the use of alternative VQE ans\"atze, based on evolutions of qubit excitation operators. Due to not accounting for fermionic anticommutation, evolutions of qubit excitation operators can be performed by circuits that require asymptotically fewer two-qubit entangling gates. Furthermore, qubit excitation operators preserve many of the physical properties of fermionic excitation operators. Performing a number of classical numerical VQE simulations for small molecules, I show that qubit-excitation-based ans\"atze can approximate molecular electronic wavefunctions almost as accurately as fermionic-excitation-based ans\"atze. Hence, I argue that evolutions of qubit excitation operators are more suitable to construct molecular ans\"atze than evolutions of fermionic excitation operators, especially in the era of NISQ computers. Motivated by the advantage of qubit-excitation-based ans\"atze, I introduce the qubit-excitation-based adaptive variational quantum eigensolver (QEB-ADAPT-VQE). The QEB-ADAPT-VQE belongs to a family of ADAPT-VQE protocols for molecular modelling that grow a problem-tailored ansatz by iteratively appending unitary operators sampled from a predefined finite-size pool of operators. The operator at each iteration is sampled based on an ansatz-growing strategy, which aims to achieve the lowest estimate for the Hamiltonian expectation value at each iteration. In this way, ADAPT-VQE protocols construct shallow-circuit, few-parameter ans\"atze tailored specifically to the molecular systems of interest. In the case of the QEB-ADAPT-VQE, the operator pool is defined by a set of evolutions of single and double qubit excitation operators. I benchmark the performance of the QEB-ADAPT-VQE, by performing classical numerical simulations. I demonstrate that it can construct ans\"atze that are several orders of magnitude more accurate, and require significantly shallower circuits, than standard UCC ans\"atze. I also compare the QEB-ADAPT-VQE against the original fermionic-ADAPT-VQE, which utilizes a pool of fermionic excitation evolutions, and the qubit-ADAPT-VQE, which utilizes a pool of Pauli-string evolutions. I demonstrate that, in terms of circuit efficiency and convergence speed, the QEB-ADAPT-VQE systematically outperforms the qubit-ADAPT-VQE, which to my knowledge was the previous most circuit-efficient, scalable VQE protocol for molecular modeling. The QEB-ADAPT-VQE protocol, therefore represents a significant improvement in the field of VQE protocols for molecular modelling and brings us closer to achieving practical quantum advantage. Lastly, I outline a modified version of the QEB-ADAPT-VQE, the excited-QEB-ADAPT-VQE, designed to estimate energies of excited molecular states. The excited-QEB-ADAPT-VQE is more robust to initial simulation conditions, at the expense of increased computational complexity.I acknowledge the funding I received from the Engineering and Physical Sciences Research Council, and Hitachi Cambridge Laborator

Breast augmentation and breast implants evolution

Female breast is a universal symbol of sexuality, motherhood and femininity today, dating back even to the time of ancient cave paintings. Historically, women have long sought breast enlargement to improve physical proportions, to foster a more feminine appearance, or to enhance self-image. When compared to the aesthetic norm, inadequate breast volume may lead to a negative body image, feelings of inadequacy, and low self-esteem. These disturbances may adversely affect a patient`s interpersonal relationships, sexual fulfillment, and quality of life. Since its introduction in 1962, modern breast augmentation with implants has become one of the most common aesthetic procedures, receiving more media attention than any other. It remains an increasingly popular surgical intervention today where the idealized female physique has morphed from the curvaceous Rubens type to one increasingly thin and androgynous, but with prominent breasts. The popularity of the procedure is thought to be based on the satisfaction of the patients` results. Breast enlargement and reshaping with breast implants nowadays is a safe, well-accepted technique, which can be undertaken with ever-less frequent complications thanks to continued advances in both surgical technique and implant design. The purpose of the present article is to make a brief review of the history of breast augmentation as a surgical procedure and the evolution of breast implants

Amniotic membrane transplantation - analysis of structural characteristics in amniotic membrane transplant and corneal ulcers

AIM: To analyze the structural characteristics in the cornea and the amniotic membrane (AM) with the help of laser scanning in-vivo confocal microscopy (IVCM) and to evaluate the morphometric changes in the cornea and the integration pattern of amniotic membrane into the host tissue using anterior-segment optical coherence tomography (AS-OCT) in patients with persistent corneal defect treated with amniotic membrane transplantation (AMT).MATERIALS AND METHODS: Nine eyes of six consecutive patients (mean age 44.9 ± 8.7 years) with corneal defects and stromal thinning unresponsive to topical treatment were enrolled in this study. Transplantation of cryopreserved amniotic membrane was performed. The time of healing of the corneal defect, morphometric analysis of the cornea and transplanted amniotic membrane using AS-OCT and the structural characteristics in the amniotic membrane grafts and corneal ulcers assessed by in vivo confocal microscopy were evaluated.RESULTS: Successful results after amniotic membrane transplantation (AMT) were observed in 8 of the 9 eyes (91.2%). On the 2nd day after transplantation, IVCM showed that under the amniotic membrane a new epithelium with large, flat, immature cells of the superficial corneal epithelium with an average density of 598.4 ± 66.38cells/mm2 was observed. The basal cells also showed immaturity and their average density was 1804 ± 93.32cells/mm2. In the corneal stroma edema and activated corneal cells were visualized. The average corneal epithelium thickness increased to 24.60 ± 2.07μm, the average density of epithelial cells increased to 657.6 ± 78.41cells/mm2, while the mean basal epithelium cells density was 2541 ± 540.13 cells/mm2. AS-OCT showed that the preoperative corneal thickness at the ulcer was 418.91 ± 96.56 μm. On the 2nd day after the surgery, the amniotic membrane (AM) thickness was measured to be 268 ±105 μm. On the 8th day it was two times smaller and was measured to be 123 ±39 μm. On the 25th day post-surgery the corneal thickness was measured at 494.03 ± 67.35 μm. In two of the cases integration of AM was found.CONCLUSIONS: AMT leads to recovery of corneal defects unresponsive to conservative treatment. The amniotic membrane graft is effective in promoting re-epithelization, nonetheless, it can also integrate into the host corneal tissue which results in an increase in corneal thickness, stabilization of the epithelium and reduction of the subjective signs. The integration of amniotic membrane into the damaged cornea proves that AMT is an effective and irreplaceable procedure for difficult-to-treat anterior ocular surface diseases

Does the Objective Matter? Comparing Training Objectives for Pronoun Resolution

Hard cases of pronoun resolution have been used as a long-standing benchmark for commonsense reasoning. In the recent literature, pre-trained language models have been used to obtain state-of-the-art results on pronoun resolution. Overall, four categories of training and evaluation objectives have been introduced. The variety of training datasets and pre-trained language models used in these works makes it unclear whether the choice of training objective is critical. In this work, we make a fair comparison of the performance and seed-wise stability of four models that represent the four categories of objectives. Our experiments show that the objective of sequence ranking performs the best in-domain, while the objective of semantic similarity between candidates and pronoun performs the best out-of-domain. We also observe a seed-wise instability of the model using sequence ranking, which is not the case when the other objectives are used.Comment: Accepted to the EMNLP 2020 conferenc

Bird-Eye Transformers for Text Generation Models

Transformers have become an indispensable module for text generation models since their great success in machine translation. Previous works attribute the~success of transformers to the query-key-value dot-product attention, which provides a robust inductive bias by the fully connected token graphs. However, we found that self-attention has a severe limitation. When predicting the (i+1)-th token, self-attention only takes the i-th token as an information collector, and it tends to give a high attention weight to those tokens similar to itself. Therefore, most of the historical information that occurred before the i-th token is not taken into consideration. Based on this observation, in this paper, we propose a new architecture, called bird-eye transformer(BET), which goes one step further to improve the performance of transformers by reweighting self-attention to encourage it to focus more on important historical information. We have conducted experiments on multiple text generation tasks, including machine translation (2 datasets) and language models (3 datasets). These experimental~results show that our proposed model achieves a better performance than the baseline transformer architectures on~all~datasets. The code is released at: \url{https://sites.google.com/view/bet-transformer/home}