Investigation of Robustness of Nanoelectronic Structures Based on Resonant Tunneling Elements

Multi-input logic gates based on two-level logic cells MOBILE have short (picosecond) switching times and higher functionality due to the ability to implement logic functions with fewer gates. This creates good prospects for the development of ultra-high-speed FPGAs with a high degree of integration, which are required for organizing high-performance computing. However, the extremely high sensitivity of resonant tunneling elements to changes in the energies of quantum states requires an assessment of the stability of such structures to external influences in real operation. In this work, the problem of assessing the stability of nanoelectronic structures that include resonant tunneling elements is considered. The method for studying the robustness of logic cells MOBILE based on a resonant tunneling diode and an НВТ transistor was proposed, making it possible to find an external interval estimate of the output voltage of the device under study for given interval models of the initial components. The technique is based on the use of systems of topological and parametric equations written in finite increments. It was shown that the proposed decomposition principle for the initial interval model ensures the algorithmic solvability of the problem posed. A computational algorithm for calculating processes in a two-level logical cell MOBILE has been developed. The algorithm provides for step-by-step integration of interval differential equations and solution of interval nonlinear algebraic equations at each step of integration using Kaucher interval arithmetic. The obtained results of the study of processes in a two-level logic cell MOBILE create prerequisites for expanding the field of application of resonant tunneling devices in high-speed monolithic integrated circuits.

CT appearances, patterns of progression, and follow-up of COVID-19: evaluation on thin-section CT

Background To retrospectively analyze CT appearances and progression pattern of COVID-19 during hospitalization, and analyze imaging findings of follow-up on thin-section CT. Methods CT findings of 69 patients with COVID-19 were evaluated on initial CT, peak CT, and pre-discharge CT. CT pattern were divided into four types on CT progression. Lesion percentage of pulmonary lobe (lobe score) was graded. Correlation analysis was made between scores and intervals. 53 patients were followed up by CT. Results Among 69 patients, 33.3% exhibited improvement pattern, 65.2% peak pattern, 1.5% deterioration pattern, and 0% fluctuation pattern. The lobe scores were positively correlated with most of intervals. It was more common to observe consolidation, pleural thickening and pleural effusion on the peak CT, and irregular line and reticulation on pre-discharge CT. The peak-initial interval were shortened when the initial CT with consolidation and pleural thickening. The intervals were extended when the irregular lines appeared on peak CT and reticulation on pre-discharge CT. Among 53 follow-up patients, 37.7% showed normal chest CT, and 62.3% showed viral pneumonia remained that mainly included GGO (100.0%) and irregular lines (33.3%). Conclusions COVID-19 displayed different appearances on CT as progressing. The peak pattern was the most common progression pattern. The CT appearances showed closely related to the intervals. The COVID-19 pneumonia can be remained or completely absorbed on CT with follow-up.

Automatic approximation using asymptotically optimal adaptive interpolation

We present an asymptotic analysis of adaptive methods for Lp approximation of functions f ∈ Cr([a, b]), where $1\le p\le +\infty $ 1 ≤ p ≤ + ∞ . The methods rely on piecewise polynomial interpolation of degree r − 1 with adaptive strategy of selecting m subintervals. The optimal speed of convergence is in this case of order m−r and it is already achieved by the uniform (nonadaptive) subdivision of the initial interval; however, the asymptotic constant crucially depends on the chosen strategy. We derive asymptotically best adaptive strategies and show their applicability to automatic Lp approximation with a given accuracy ε.

SEMBLANCE RESIDUAL MOVEOUT ANALYSIS TO FIND ERORRS AND UPDATING THE INTERVAL VELOCITY MODEL MODE IN THE HORIZON BASED TOMOGRAPHY METHOD

The tomography method requires an excellent initial velocity model. On the horizon based tomography, it will correct the travel time error of seismic waves along the horizon which is analysed using input results from the analysis of residual depth moveout. In this study, a semblance residual moveout analysis will be conducted after the interval velocity model has applied to the SBI field seismic data (CDP Gathers and RMS velocity). Based on the imaging results generated by the PSDM running process, an aperture value of 550 for inline and 800 for crossline is selected. PSDM generated from the initial interval velocity model has an acoustic impedance value between 1000 kg/m2s to 14339.2 kg/m2s. The PSDM process, residual moveout analysis, and horizon-based tomography are carried out iteratively until the error in the interval velocity model approaches zero. In this study, five iterations were performed. The resulting residual moveout is increasingly oscillating around zero after the 5th iteration, which indicates that the error in the interval velocity model is getting smaller. There are two types of residual moveout, namely residuals moveout positively and residuals moveout negatively. Residual moveout positive indicates that the velocity used is too high, while the residual moveout negative indicates that the velocity used is too low. The identification of interval velocity model errors with analysis of residual moveout semblance is calculated from depth gathers. The semblance residual moveout analysis is used for the Pre Stack Depth Migration (PSDM) depth image analysis stage along with the marker (well data). .

On approximations of the point measures associated with the Brownian web by means of the fractional step method and the discretization of the initial interval

UDC 519.21 We establish the rate of weak convergence in the fractional step method for the Arratia flow in terms of the Wasserstein distance between the images of the Lebesque measure under the action of the flow. We introduce finite-dimensional densities that describe sequences of collisions in the Arratia flow and derive an explicit expression for them. With the initial interval discretized, we also discuss the convergence of the corresponding approximations of the point measure associated with the Arratia flow in terms of such densities.

PERBANDINGAN PERAMALAN INFLASI KOTA DENPASAR MENGGUNAKAN METODE FUZZY TIME SERIES DAN MULTILAYER PERCEPTRON

ABSTRACT<br />Inflation is one of the indicator to see the economic stability of a region, which shows the development of prices of goods and services in general, calculated from the consumer price index. One way to control inflation is to use forecasts. In this study, fuzzy time series (FTS) and Multilayer perceptron (MLP) forecasting methods are used. Both of these methods will be used for forecasting with time series data. This experiment use data collected from year calendar inflation data from the Bali Central Statistics Agency in the city of Denpasar. This method will be applied to the inflation rate data for years 1990-2016. In this forecasting experiment, the Fuzzy time series actual data will be changed to the percentage change shape to determine the set of universes, determine the initial interval, determine the fuzzy interval, calculate the predicted value of the percentage and make a forecast. Forecasting results with the FTS method obtained an average value of MSE of 6.09. While the Multilayer Perceptron method, the data used in this study are 27 calendar year inflation data, of which 18 data are used in the training process and 18 data are used for the testing process. In this study, 9: 6: 1 architecture is used, where the input to the perceptron network is 9, the hidden layer is 6 pieces and 1 output. From the calculation obtained forecasting with an average MSE value of 9.8. Based on the value of the error obtained, FTS provides better forecasting results than MLP.<br />Keywords: Inflation,Multilayer Perceptron, Fuzzy Time Series.<br />ABSTRAK<br />Inflasi adalah salah satu indikator untuk melihat stabilitas ekonomi suatu wilayah atau daerah, yang menunjukkan perkembangan harga barang dan jasa secara umum yang dihitung dari indeks harga konsumen. Salah satu cara untuk mengendalikan inflasi adalah dengan menggunakan ramalan. Pada penelitian ini digunakan metode peramalan fuzzy time series(FTS) dan Multilayer perceptron(MLP). Kedua metode ini akan digunakan untuk melakukan peramalan dengan data runtutan (time series). Dimana data yang digunakan bersumber dari data inflasi tahun kalender dari Badan Pusat Statistik provinsi Bali di kota Denpasar. Metode ini akan diterapkan pada data laju inflasi tahun 1990-2016. Pada peramalan dengan metode Fuzzy time series data actual akan dirubah kebentuk persentase perubahan untuk menentukan himpunan semesta, menentukan interval awal, menentukan interval fuzzy, menghitung nilai prediksi persentase perubahan dan melakukan peramalan. Hasil peramalan dengan metode FTS diperoleh nilai rata-rata MSE sebesar 6,09. Sedangan pada metode Multilayer Perceptron, data yang digunakan pada penelitian ini adalah data inflasi tahun kalender sebanyak 27 data, dimana 18 data digunakan dalam proses testing dan 18 data digunakan untuk proses testing. Pada penelitian ini digunakan arsitektur 9:6:1, dimana input ke jaringan perceptron sebesar 9, layer tersembunyi sebanyak 6 buah dan 1 buah output. Dari hasil perhitungan didapatkan hasil peramalan dengan rata-rata nilai MSE sebesar 9,8. Berdasarkan nilai kesalahan/MSE yang diperoleh, FTS memberikan hasil peramalan yang lebih baik dibandingkan MLP.<br />Kata Kunci : Inflasi, Multilayer Perceptron, Fuzzy Time Series.

Equisum Partitions of Sets of Positive Integers

Let V be a finite set of positive integers with sum equal to a multiple of the integer b. When does V have a partition into b parts so that all parts have equal sums? We develop algorithmic constructions which yield positive, albeit incomplete, answers for the following classes of set V, where n is a given positive integer: (1) an initial interval a∈Z+:a≤n; (2) an initial interval of primes p∈P:p≤n, where P is the set of primes; (3) a divisor set d∈Z+:d|n; (4) an aliquot set d∈Z+:d|n, d<n. Open general questions and conjectures are included for each of these classes.

Optimization of systemic juvenile arthritis treatment regimens with correction of tocilizumab intravenous administration according to data of observational retrospective study

Objective: to assess the possibility of using varying interval between intravenous infusions of tocilizumab (TCZ) as a tool for choosing the optimal treatment regimen in systemic juvenile arthritis (SJA).Subjects and methods. The observational retrospective study included 72 patients (29 boys and 43 girls) with a SJA fulfilled ILAR criteria, who received TCZ ≥12 months, in which previous therapy with various anti-rheumatic drugs was ineffective. We studied the changes of the main clinical and laboratory parameters of the SJA activity after correction of the interval between infusions.Results and discussion. In the studied group median age of onset was 3.8 [2.1; 5.9] years, duration of disease before the appointment of TCZ – 26.5 [9.25; 62.25] months. Therapy is continued by 70 patients, the median duration of therapy is 5.0 [2.75; 6.38] years. The initial interval between TCZ infusions was 2 weeks in 49 (group 1) and 4 weeks in 23 patients (group 2). After 6 months of therapy in group 2, the interval was reduced to 2 weeks in 15 (65.2%) patients due to decreased effectiveness. Prolongation of the period between the introduction of TCZ in patients of group 1 who did not reach the inactive status of the disease in the 1st year of the disease resulted in a significant increase of erythrocyte sedimentation rate, C-reactive protein level and exacerbation of systemic manifestations of SJA (p<0.01) in the absence of statistically significant changes of joint status parameters (p>0.05). 40% of these patients had involvement of «new» joints, including hip joints. «Harbingers» of exacerbation in the period of increasing intervals between infusions were: arthralgia (88%), myalgia (65%), sore throat (30%), dysphoria (50%, more often in preschool children), increase of ferritin level and number of leukocytes. In 90.3% of patients who have reached the inactive status of the disease, it was possible to gradually increase the interval between infusions. In 6 patients, TCZ was canceled by gradually increasing the intervals, in 4 of them, therapy was resumed at an initial interval of 2 weeks after 3, 6, 21 and 22 months, respectively, in two patients, a drug-free remission was maintained during 23 and 20 months. Reduction of intervals to the initial 2 weeks was performed in 13 (18.1%) patients. The development of exacerbations with the need to reduce the interval to the initial one was most often observed at 24–35 months of therapy, which chronologically coincided with the period of active growth. Currently, 15 patients receiving TCZ with an interval of 5–6 weeks, and 40 – with an interval of 4 weeks, 9 patients – 3 weeks, in 6 patients attempt to increase the interval to more than 2–2,5 weeks was unsuccessful.Conclusion. Experience suggests the need to comply with a two-week interval between infusions of TCZ at the initial stage of therapy in most patients with SJA until the inactive stage of the disease, followed by a smooth individual increase in the interval to 4 weeks (2–3 days under careful medical supervision). Appearance of initial signs of exacerbation, requires to reduce the interval to 2 weeks. Before deciding on the complete withdrawal of TCZ, it is advisable to increase the interval between infusions to 5–6 weeks under careful clinical and laboratory control.

Method Comparison of Model Based Tomography and Grid Based Tomography to refine interval velocity

<span>The input data for pre stack time migration and pre stack depth migration is velocity model. <span>The exact velocity model can provide maximum result in seismic section. The best seismic <span>section can minimize possibility of errors during interpretation. Model based and grid based <span>tomography are used to refine the interval velocity model. The interval velocity will be used as <span>input in the pre stack depth migration. Initial interval velocity is obtained from RMS velocity<br /><span>using Dix formula. This velocity will be refined by global depth tomography method. The <span>global depth tomography method is divided into model based and grid based tomography. <span>Velocity analysis is performed along the horizon (depth model). Residual depth move out is <span>obtained from picking velocity. It is used as input in tomography method. The flat gather is <span>obtained at tenth iteration. The interval velocity that is obtained from tenth iteration has the <span>small errors. Tomography method can provide maximum result on velocity refinement. That is <span>shown by the result that the pre stack depth migration is much better than using initial interval <span>velocity. The pull up effect can be corrected by tomography method.</span></span></span></span></span></span></span></span></span></span></span></span><br /></span>