Сучасні підходи до формування системи регулювання інноваційного розвитку регіонів

Статья посвящена проблеме формирования концептуальных и методологических аспектов усовершенствования организационно-экономического механизма системы регулирования инновационного развития регионов. В статье предложены принципы формирования такой системы, выделены блоки стратегии, которые требуют особого внимания и предложены направления их реализации.Стаття присвячена проблемі формування концептуальних та методологічних аспектів удосконалення організаційно-економічного механізму системи регулювання інноваційного розвитку регіонів. У статті запропоновано принципи формування такої системи, виділено блоки стратегії, що вимагають особливої уваги і запропоновано напрямки їхньої реалізації.The article is devoted to the problem the formation of conceptual and methodological aspects of improvement on organized-economical mechanism of the regulation system in innovative development of the regions. The principles of formation in such system, the strategies which need special attention and the directions in their realization are proposed in this article

Effects of the Spacer Length on the High-Frequency Nanoscale Field Effect Diode performance

Abstract The performance of nanoscale Field Effect Diodes as a function of the spacer length between two gates is investigated. Our numerical results show that the I on /I off ratio which is a significant parameter in digital application can be varied from 10 1 to 10 4 for S-FED as the spacer length between two gates increases whereas this ratio is approximately constant for M-FED. The high-frequency performance of FEDs is investigated and the cut-off frequency of the intrinsic transistor without parasitic capacitance is calculated. The figures of merit including intrinsic gate delay time and energy-delay product have been studied for the field effect diodes which are interesting candidates for future logic applications. JNS All rights reserve

Long-Term Macroeconomic Effects of Climate Change: A Cross-Country Analysis

We study the long-term impact of climate change on economic activity across countries, using a stochastic growth model where labour productivity is affected by country-specific climate variables—-defined as deviations of temperature and precipitation from their historical norms. Using a panel data set of 174 countries over the years 1960 to 2014, we find that per-capita real output growth is adversely affected by persistent changes in the temperature above or below its historical norm, but we do not obtain any statistically significant effects for changes in precipitation. Our counterfactual analysis suggests that a persistent increase in average global temperature by 0.04°C per year, in the absence of mitigation policies, reduces world real GDP per capita by 7.22 percent by 2100. On the other hand, abiding by the Paris Agreement, thereby limiting the temperature increase to 0.01°C per annum, reduces the loss substantially to 1.07 percent. These effects vary significantly across countries. We also provide supplementary evidence using data on a sample of 48 U.S. states between 1963 and 2016, and show that climate change has a long-lasting adverse impact on real output in various states and economic sectors, and on labour productivity and employment

Pogostone effect on dacarbazine-induced autophagy and apoptosis in human melanoma cells

Objective: Chemotherapy is effective for treating malignant melanoma, but drug resistance and occurrence of side effects limited this strategy. The balance between autophagy and apoptosis has an essential role in the chemotherapy of cancers. The present investigation aims to examine the efficacy of pogostone (isolated from Pogostemon cablin L.) on the ratio of apoptosis and autophagy caused by dacarbazine in melanoma cells. Materials and Methods: Human melanoma cells were exposed to different concentrations of dacarbazine and pogostone, and the IC50 values were calculated. The cells were treated with two concentrations higher and lower than IC50 simultaneously, and the dose reduction index and combination index (CI) parameters were calculated. The occurrence of apoptosis and autophagy was evaluated. The expression level of genes related to apoptosis and autophagy pathways was tested. Results: Pogostone and dacarbazine declined the number of the cells in a dose and time-dependent manner and showed a synergistic effect. There was a significant decrease in autophagy in the co-treatment besides the dacarbazine alone (p < 0.05). There was a considerable increment in apoptosis in cultures treated with pogostone and dacarbazine (p < 0.05). Also, Real-time PCR data confirmed the obtained results. Conclusions: Pogostone reduced melanoma cell resistance to dacarbazine via autophagy blockage

Towards a hybrid computational strategy based on Deep Learning for incompressible flows

The Poisson equation is present in very different domains of physics and engineering. In most cases, this equation can not be solved directly and iterative solvers are used. For many solvers, this step is computationally intensive. In this study, an alternative resolution method based on neural networks is evaluated for incompressible flows. A fluid solver coupled with a Convolutional Neural Network is developed and trained on random cases with constant density to predict the pressure field. Its performance is tested in a plume configuration, with different buoyancy forces, parametrized by the Richardson number. The neural network is compared to a traditional Jacobi solver. The performance improvement is considerable, although the accuracy of the network is found to depend on the flow operating point: low errors are obtained at low Richardson numbers, whereas the fluid solver becomes unstable with large errors for large Richardson number. Finally, a hybrid strategy is proposed in order to benefit from the calculation acceleration while ensuring a user-defined accuracy level. In particular, this hybrid CFD-NN strategy, by maintaining the desired accuracy whatever the flow condition, makes the code stable and reliable even at large Richardson numbers for which the network was not trained for. This study demonstrates the capability of the hybrid approach to tackle new flow physics, unseen during the network training

A novel physics informed deep learning method for simulation-based modelling

In this paper, we present a brief review of the state of the art physics informed deep learning methodology and examine its applicability, limits, advantages, and disadvantages via several applications. The main advantage of this method is that it can predict the solution of the partial differential equations by using only boundary and initial conditions without the need for any training data or pre-process phase. Using physics informed neural network algorithms, it is possible to solve partial differential equations in many different problems encountered in engineering studies with a low cost and time instead of traditional numerical methodologies. A direct comparison between the initial results of the current model, analytical solutions, and computational fluid dynamics methods shows very good agreement. The proposed methodology provides a crucial basis for solution of more advance partial differential equation systems and offers a new analysis and mathematical modelling tool for aerospace application

Search for transient optical counterparts to high-energy IceCube neutrinos with Pan-STARRS1

In order to identify the sources of the observed diffuse high-energy neutrino flux, it is crucial to discover their electromagnetic counterparts. IceCube began releasing alerts for single high-energy ($E > 60$ TeV) neutrino detections with sky localisation regions of order 1 deg radius in 2016. We used Pan-STARRS1 to follow-up five of these alerts during 2016-2017 to search for any optical transients that may be related to the neutrinos. Typically 10-20 faint ($m < 22.5$ mag) extragalactic transients are found within the Pan-STARRS1 footprints and are generally consistent with being unrelated field supernovae (SNe) and AGN. We looked for unusual properties of the detected transients, such as temporal coincidence of explosion epoch with the IceCube timestamp. We found only one transient that had properties worthy of a specific follow-up. In the Pan-STARRS1 imaging for IceCube-160427A (probability to be of astrophysical origin of $\sim$50 %), we found a SN PS16cgx, located at 10.0' from the nominal IceCube direction. Spectroscopic observations of PS16cgx showed that it was an H-poor SN at z = 0.2895. The spectra and light curve resemble some high-energy Type Ic SNe, raising the possibility of a jet driven SN with an explosion epoch temporally coincident with the neutrino detection. However, distinguishing Type Ia and Type Ic SNe at this redshift is notoriously difficult. Based on all available data we conclude that the transient is more likely to be a Type Ia with relatively weak SiII absorption and a fairly normal rest-frame r-band light curve. If, as predicted, there is no high-energy neutrino emission from Type Ia SNe, then PS16cgx must be a random coincidence, and unrelated to the IceCube-160427A. We find no other plausible optical transient for any of the five IceCube events observed down to a 5$\sigma$ limiting magnitude of $m \sim 22$ mag, between 1 day and 25 days after detection.Comment: 20 pages, 6 figures, accepted to A&

Neutrinos below 100 TeV from the southern sky employing refined veto techniques to IceCube data

Many Galactic sources of gamma rays, such as supernova remnants, are expected to produce neutrinos with a typical energy cutoff well below 100 TeV. For the IceCube Neutrino Observatory located at the South Pole, the southern sky, containing the inner part of the Galactic plane and the Galactic Center, is a particularly challenging region at these energies, because of the large background of atmospheric muons. In this paper, we present recent advancements in data selection strategies for track-like muon neutrino events with energies below 100 TeV from the southern sky. The strategies utilize the outer detector regions as veto and features of the signal pattern to reduce the background of atmospheric muons to a level which, for the first time, allows IceCube searching for point-like sources of neutrinos in the southern sky at energies between 100 GeV and several TeV in the muon neutrino charged current channel. No significant clustering of neutrinos above background expectation was observed in four years of data recorded with the completed IceCube detector. Upper limits on the neutrino flux for a number of spectral hypotheses are reported for a list of astrophysical objects in the southern hemisphere.Comment: 19 pages, 17 figures, 2 table