Ant Lion Optimization algorithm for kidney exchanges.

The kidney exchange programs bring new insights in the field of organ transplantation. They make the previously not allowed surgery of incompatible patient-donor pairs easier to be performed on a large scale. Mathematically, the kidney exchange is an optimization problem for the number of possible exchanges among the incompatible pairs in a given pool. Also, the optimization modeling should consider the expected quality-adjusted life of transplant candidates and the shortage of computational and operational hospital resources. In this article, we introduce a bio-inspired stochastic-based Ant Lion Optimization, ALO, algorithm to the kidney exchange space to maximize the number of feasible cycles and chains among the pool pairs. Ant Lion Optimizer-based program achieves comparable kidney exchange results to the deterministic-based approaches like integer programming. Also, ALO outperforms other stochastic-based methods such as Genetic Algorithm in terms of the efficient usage of computational resources and the quantity of resulting exchanges. Ant Lion Optimization algorithm can be adopted easily for on-line exchanges and the integration of weights for hard-to-match patients, which will improve the future decisions of kidney exchange programs. A reference implementation for ALO algorithm for kidney exchanges is written in MATLAB and is GPL licensed. It is available as free open-source software from: https://github.com/SaraEl-Metwally/ALO_algorithm_for_Kidney_Exchanges

Unimodal‐Bio‐GAN: Keyless biometric salting scheme based on generative adversarial network

Abstract Cancellable biometrics enabled us to develop robust authentication systems by replacing the storage of the original biometric template with another secured version. A technique called biometric salting uses a parameter (key) and an invertible function to transform the human biometrics features into a secured format that can be protected and stored securely in a biometric database system. The salting key plays a main role in the success of this transformation, which makes it robust or vulnerable to many security attacks. One of the main challenges that faces biometrics' researchers currently is how to design and protect such a salting key considering two basic measures: security and recognition accuracy. In this article, we propose unimodal‐Bio‐GAN, a reliable keyless biometric salting technique based on standard generative adversarial network (GAN). In unimodal‐Bio‐GAN, a random permuted version of the human biometric data is implicitly considered as a salting key and required only during the enrolment stage, which increases the system reliability to overcome different security attacks. The experimental results of unimodal‐Bio‐GAN using the CASIA Iris‐V3‐Internal database outperform the previous methods and its security efficiency is analysed using different attack types

Multiple Bilateral Ovarian Mature Cystic Teratomas with Ovarian Torsion: A Case Report

Ovarian tumors are a common form of neoplasm in women. Mature cystic teratoma is the most common type, with a bilateral incidence of 8–15%. However, few cases are reported as bilateral and multiple. A rare case of bilateral multiple dermoid cysts in a 19-year-old female patient presented with abdominal pain of one-day duration. Her medical history was unremarkable. Ultrasonography showed multiple bilateral ovarian cystic masses. The patient underwent laparotomy. The masses were excised while preserving the remaining ovarian tissue. Histopathology confirmed the diagnosis of multiple mature cystic teratomas with no presence of malignant tissue

A NEAD exchange graph.

<p>A chain starts with an altruistic donor and ends with a bridge donor assigned to the first compatible patient on the next round.</p

A directed graph representation of three-cycle exchange.

<p>The solid arcs represent the potential swaps, i.e. the two pairs (,) and (,) can exchange their kidneys.</p

Number of transplants (with) and without the proposed post-processing step for various KPD pool sizes.

<p>Number of transplants (with) and without the proposed post-processing step for various KPD pool sizes.</p

Elite individual’s fitness per iteration.

<p>Elite individual’s fitness per iteration.</p

Compatibility information with respect to the pool size, n.

<p>Compatibility information with respect to the pool size, n.</p

The composition of a resulting optimal solution.

<p>(a) IP-KPD, (b) Proposed, (c) GA-KPD.</p

Parameter settings for GA-KPD and the proposed method.

<p>Parameter settings for GA-KPD and the proposed method.</p