Foreign policy orientation of Turkey's pro-Islamist parties: A comparative study of the AKP and Refah

This study aims to discuss the foreign policies of the pro-Islamist parties in Turkey by comparing the party programs and policies of the Justice and Development Party (Adalet ve Kalkınma Partisi) and the Welfare Party (Refah Partisi). By focusing on programs and policies separately, it is argued that pro-Islamist elements in the establishment and program of the parties do not necessarily translate to actual policies, particularly in foreign affairs. Moreover, pro-Islamist political parties are not monolithic in terms of member composition; the parties also differ from each other. Finally, the parties might have different policies in the domestic context while employing a more pragmatic and traditionalist perspective in terms of foreign policy

Preparing thermal states of quantum systems by dimension reduction

We present an algorithm that prepares thermal Gibbs states of one dimensional quantum systems on a quantum computer without any memory overhead, and in a time significantly shorter than other known alternatives. Specifically, the time complexity is dominated by the quantity $N^{\|h\|/ T}$, where $N$ is the size of the system, $\|h\|$ is a bound on the operator norm of the local terms of the Hamiltonian (coupling energy), and $T$ is the temperature. Given other results on the complexity of thermalization, this overall scaling is likely optimal. For higher dimensions, our algorithm lowers the known scaling of the time complexity with the dimension of the system by one.Comment: Published version. Minor editorial changes, one new reference added. 4 pages, 1 figur

Anyonic entanglement renormalization

We introduce a family of variational ansatz states for chains of anyons which optimally exploits the structure of the anyonic Hilbert space. This ansatz is the natural analog of the multi-scale entanglement renormalization ansatz for spin chains. In particular, it has the same interpretation as a coarse-graining procedure and is expected to accurately describe critical systems with algebraically decaying correlations. We numerically investigate the validity of this ansatz using the anyonic golden chain and its relatives as a testbed. This demonstrates the power of entanglement renormalization in a setting with non-abelian exchange statistics, extending previous work on qudits, bosons and fermions in two dimensions.Comment: 19 pages, 10 figures, v2: extended, updated to match published versio

Attack Type Agnostic Perceptual Enhancement of Adversarial Images

Adversarial images are samples that are intentionally modified to deceive machine learning systems. They are widely used in applications such as CAPTHAs to help distinguish legitimate human users from bots. However, the noise introduced during the adversarial image generation process degrades the perceptual quality and introduces artificial colours; making it also difficult for humans to classify images and recognise objects. In this letter, we propose a method to enhance the perceptual quality of these adversarial images. The proposed method is attack type agnostic and could be used in association with the existing attacks in the literature. Our experiments show that the generated adversarial images have lower Euclidean distance values while maintaining the same adversarial attack performance. Distances are reduced by 5.88% to 41.27% with an average reduction of 22% over the different attack and network types

Wheat bread with dairy products - Technology, nutritional and sensory properties

Featured Application: Bakery industry, as nutritional and functional breads, with a considerable contribution to balance the daily diet for children and seniors in terms of proteins and mineralsAs the relation between diet and health became a priority for the consumers, the development of healthy foods enriched with functional ingredients increased substantially. Dairy products represent an alternative for new products and can be used to enhance the functional and nutritional value of bakery products. The addition of yoghurt and curd cheese to wheat bread was studied, and the impact on the dough rheology, microstructure, bread quality, and sensory properties were evaluated. Dairy product additions from 10 to 50 g and higher levels up to 70 g of yoghurt and 83 g of curd cheese were tested. Replacements were performed on wheat flour basis and water absorption. It was observed that the yoghurt additions had a positive impact on the rheology characteristics of the dough. For curd cheese additions, the best dough evaluated on extension was the 30 g of wheat flour formulation. In both cases, the microstructure analysis supported the results obtained for doughs and breads. These breads showed a significant improvement on nutrition profile, which is important to balance the daily diet in terms of major and trace minerals and is important for health-enhancing and maintenance. Good sensorial acceptability for breads with 50 g of yoghurt and 30 g of curd cheese was obtainedinfo:eu-repo/semantics/publishedVersio

Coarse grained belief propagation for simulation of interacting quantum systems at all temperatures

We continue our numerical study of quantum belief propagation initiated in [Phys. Rev. A, 77 (2008), p. 052318]. We demonstrate how the method can be expressed in terms of an effective thermal potential that materializes when the system presents quantum correlations, but is insensitive to classical correlations. The thermal potential provides an efficient means to assess the precision of belief propagation on graphs with no loops. We illustrate these concepts using the one-dimensional quantum Ising model and compare our results with exact solutions. We also use the method to study the transverse field quantum Ising spin glass for which we obtain a phase diagram that is largely in agreement with the one obtained in [arXiv:0706.4391] using a different approach. Finally, we introduce the coarse grained belief propagation (CGBP) algorithm to improve belief propagation at low temperatures. This method combines the reliability of belief propagation at high temperatures with the ability of entanglement renormalization to efficiently describe low energy subspaces of quantum systems with local interactions. With CGBP, thermodynamic properties of quantum systems can be calculated with a high degree of accuracy at all temperatures.Comment: updated references and acknowledgement

Brain Categorization: Learning, Attention, and Consciousness

How do humans and animals learn to recognize objects and events? Two classical views are that exemplars or prototypes are learned. A hybrid view is that a mixture, called rule-plus-exceptions, is learned. None of these models learn their categories. A distributed ARTMAP neural network with self-supervised learning incrementally learns categories that match human learning data on a class of thirty diagnostic experiments called the 5-4 category structure. Key predictions of ART models have received behavioral, neurophysiological, and anatomical support. The ART prediction about what goes wrong during amnesic learning has also been supported: A lesion in its orienting system causes a low vigilance parameter.Air Force Office of Scientific Research (F49620-01-1-0397, F49620-01-1-0423); Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-01-1-0624), the National Geospatial Intelligence Agency (NMA 201-01-1-2016); National Science Foundation (EIA-01-30851, IIS-97-20333, SBE-0354378); Office of Naval Research (N00014-95-1-0657, N00014-01-1-0624