ERKEN UYARI SISTEMLERÝ YOLUYLA TURKIYE’DEKI EKONOMIK KRIZLERIN ANALIZI

It is observed that the interest rate-exchange rate nexus in the Turkish economy appeared in the process of financial liberalization has formed a fragile structure and that this situation has triggered the economic crises along with the rising of the country’s risk premium. In this context, the attentions have been drawn up on the crises which were led by the artificial welfare increases created by the gap between interest rate and exchange rate, and up on the unsustainability of artificially appreciated national currency with high interest rates in the economy.Economic crises, Currency-balance of payment crises, Financial-banking crises, Early warning systems, exchange rate pressure index, Turkish economy, Logit model, Probit model

A Cost-efficient IoT Forensics Framework with Blockchain

IoT devices have been adopted widely in the last decade which enabled collection of various data from different environments. The collected data is crucial in certain applications where IoT devices generate data for critical infrastructure or systems whose failure may result in catastrophic results. Specifically, for such critical applications, data storage poses challenges since the data may be compromised during the storage and the integrity might be violated without being noticed. In such cases, integrity and data provenance are required in order to be able to detect the source of any incident and prove it in legal cases if there is a dispute with the involved parties. To address these issues, blockchain provides excellent opportunities since it can protect the integrity of the data thanks to its distributed structure. However, it comes with certain costs as storing huge amount of data in a public blockchain will come with significant transaction fees. In this paper, we propose a highly cost effective and reliable digital forensics framework by exploiting multiple inexpensive blockchain networks as a temporary storage before the data is committed to Ethereum. To reduce Ethereum costs,we utilize Merkle trees which hierarchically stores hashes of the collected event data from IoT devices. We evaluated the approach on popular blockchains such as EOS, Stellar, and Ethereum by presenting a cost and security analysis. The results indicate that we can achieve significant cost savings without compromising the integrity of the data

Double-Free-Layer Stochastic Magnetic Tunnel Junctions with Synthetic Antiferromagnets

Stochastic magnetic tunnel junctions (sMTJ) using low-barrier nanomagnets have shown promise as fast, energy-efficient, and scalable building blocks for probabilistic computing. Despite recent experimental and theoretical progress, sMTJs exhibiting the ideal characteristics necessary for probabilistic bits (p-bit) are still lacking. Ideally, the sMTJs should have (a) voltage bias independence preventing read disturbance (b) uniform randomness in the magnetization angle between the free layers, and (c) fast fluctuations without requiring external magnetic fields while being robust to magnetic field perturbations. Here, we propose a new design satisfying all of these requirements, using double-free-layer sMTJs with synthetic antiferromagnets (SAF). We evaluate the proposed sMTJ design with experimentally benchmarked spin-circuit models accounting for transport physics, coupled with the stochastic Landau-Lifshitz-Gilbert equation for magnetization dynamics. We find that the use of low-barrier SAF layers reduces dipolar coupling, achieving uncorrelated fluctuations at zero-magnetic field surviving up to diameters exceeding ($D\approx 100$ nm) if the nanomagnets can be made thin enough ($\approx 1$-$2$ nm). The double-free-layer structure retains bias-independence and the circular nature of the nanomagnets provides near-uniform randomness with fast fluctuations. Combining our full sMTJ model with advanced transistor models, we estimate the energy to generate a random bit as $\approx$ 3.6 fJ, with fluctuation rates of $\approx$ 3.3 GHz per p-bit. Our results will guide the experimental development of superior stochastic magnetic tunnel junctions for large-scale and energy-efficient probabilistic computation for problems relevant to machine learning and artificial intelligence

Paraesthesia Caused by the Separated Endodontic Instrument: Case Report

Abstract In endodontics, separated endodontic instruments located in the mandibular canal may cause an injury of the inferior alveolar nerve (IAN) resulting in disabling sensory disturbances such as pain, paraesthesia, and dysaesthesia of the lower lip and chin area. In clinically paraesthesia usually manifests as numbness, tingling or any deviation from normal sensation. The suggested therapeutic sequence for endodontic related paraesthesia is the control of pain and inflammation and, whenever possible, the surgical elimination of the cause. A healthy 33-yearold woman was referred to the Department of Endodontics, Oral and Dental Healthy Hospital, Eskişehir suffering from pain and paraesthesia in the left lower lip and chin. Radiographic examination revealed the presence of a separated endodontic instrument beyond the apex of the mandibular left second molar and this instrument was inside the left mandibular canal. Damage to the IAN secondary to extrusion of a separated endodontic instrument was diagnosed. Extraction of the tooth was decided and after prednisone and pregabalin treatments both pain and paraesthesia on the left side of the lower lip and chin were gone

Hypotension, Syncope, and Fever in Systemic Mastocytosis without Skin Infiltration and Rapid Response to Corticosteroid and Cyclosporin: A Case Report

Mast cell disorders are defined by an abnormal accumulation of tissue mast cells in one or more organ systems. In systemic mastocytosis, at least one extracutaneous organ is involved by definition. Although, systemic mastocytosis usually represents with skin lesion called urticaria pigmentosa, in a small proportion, there is extracutaneous involvement without skin infiltration. Other manifestations are flushing, tachycardia, dyspepsia, diarrhea, hypotension, syncope, and rarely fever. Various medications have been used but there is not a definite cure for systemic mastocytosis. The principles of treatment include control of symptoms with measures aimed to decrease mast cell activation. We describe a case of systemic mastocytosis presenting with hypotension, syncope attacks, fever, and local flushing. In bone marrow biopsy, increased mast cell infiltration was demonstrated. She had no skin infiltration. A good clinicopathological response was obtained acutely with combination therapy of glucocorticoid and cyclosporine

CMOS + stochastic nanomagnets: heterogeneous computers for probabilistic inference and learning

Extending Moore's law by augmenting complementary-metal-oxide semiconductor (CMOS) transistors with emerging nanotechnologies (X) has become increasingly important. Accelerating Monte Carlo algorithms that rely on random sampling with such CMOS+X technologies could have significant impact on a large number of fields from probabilistic machine learning, optimization to quantum simulation. In this paper, we show the combination of stochastic magnetic tunnel junction (sMTJ)-based probabilistic bits (p-bits) with versatile Field Programmable Gate Arrays (FPGA) to design a CMOS + X (X = sMTJ) prototype. Our approach enables high-quality true randomness that is essential for Monte Carlo based probabilistic sampling and learning. Our heterogeneous computer successfully performs probabilistic inference and asynchronous Boltzmann learning, despite device-to-device variations in sMTJs. A comprehensive comparison using a CMOS predictive process design kit (PDK) reveals that compact sMTJ-based p-bits replace 10,000 transistors while dissipating two orders of magnitude of less energy (2 fJ per random bit), compared to digital CMOS p-bits. Scaled and integrated versions of our CMOS + stochastic nanomagnet approach can significantly advance probabilistic computing and its applications in various domains by providing massively parallel and truly random numbers with extremely high throughput and energy-efficiency