Economic tools for realization of methane production project on Kuzbass coal deposits

Environmental issues and, above all, issues related to the release of greenhouse gases into the atmosphere, such as coal bed methane, actualize the challenge of searching a variety of options for its disposal. The difference in the macroeconomic, industrial, geological and infrastructural features determine the need to choose the most cost-effective option for using of methane emitted from the coal deposits. Various economic ways to improve the profitability of production are viewed on the basis of the analysis of methane production project from Kuzbass coal deposits, Kemerovo region, Russia

Production operation of small petroleum enterprises in Tomsk region

Implementing resource-innovative strategy to develop Russian fuel-and-energy sector implies the promotion of small oil production enterprises developing fields with the reserves of less than 5 mln. tons. However, the efficiency of such enterprises, investigated on the example of Tomsk region (considering the indexes of oil extraction, growth of reserves, amount of capital expenditures and geological surveys), signifies the presence of definite tendencies. Consequently, management decisions concerning economic, organizational, financial and fiscal character should be taken in order to eliminate detrimental factors

Delivery of IL-35 by Lactococcus lactis Ameliorates Collagen-Induced Arthritis in Mice

IL-35, a relatively newly discovered cytokine belonging to the larger IL-12 family, shows unique anti-inflammatory properties, believed to be associated with dedicated receptors and signaling pathways. IL-35 plays a pivotal role in the development and the function of both regulatory B (Bregs) and T cells (Tregs). In order to further its therapeutic potential, a dairy Lactococcus lactis strain was engineered to express murine IL-35 (LL-IL35), and this recombinant strain was applied to suppress collagen-induced arthritis (CIA). Oral administration of LL-IL35 effectively reduced the incidence and disease severity of CIA. When administered therapeutically, LL-IL35 abruptly halted CIA progression with no increase in disease severity by reducing neutrophil influx into the joints. LL-IL35 treatment reduced IFN-γ and IL-17 3.7- and 8.5-fold, respectively, and increased IL-10 production compared to diseased mice. Foxp3+ and Foxp3− CD39+ CD4+ T cells were previously shown to be the Tregs responsible for conferring protection against CIA. Inquiry into their induction revealed that both CCR6+ and CCR6− Foxp3+or− CD39+ CD4+ T cells act as the source of the IL-10 induced by LL-IL35. Thus, this study demonstrates the feasibility and benefits of engineered probiotics for treating autoimmune diseases

Trees classification based on Fourier coefficients of the sapflow density flux

In this paper we study the possibility to use the artificial neural networks for trees classification based on real and approximated values of the sap flow density flux describing water transport in trees. The data sets were generated by means of a new tree monitoring system TreeTalker. The Fourier series-based model is used for fitting the data sets with periodic patterns. The multivariate regression model defines the functional dependencies between sap flow density and temperature time series. The paper shows that Fourier coefficients can be successfully used as elements of the feature vectors required to solve different classification problems. Here we train multilayer neural networks to classify the trees according to different types of classes. The quality of the developed model for prediction and classification is verified by numerous numerical examples

Trees classification based on Fourier coefficients of the sapflow density flux

In this paper we study the possibility to use the artificial neural networks for trees classification based on real and approximated values of the sap flow density flux describing water transport in trees. The data sets were generated by means of a new tree monitoring system TreeTalker. The Fourier series-based model is used for fitting the data sets with periodic patterns. The multivariate regression model defines the functional dependencies between sap flow density and temperature time series. The paper shows that Fourier coefficients can be successfully used as elements of the feature vectors required to solve different classification problems. Here we train multilayer neural networks to classify the trees according to different types of classes. The quality of the developed model for prediction and classification is verified by numerous numerical examples

Динамика маркеров стресс-реакции при эмболизации маточных артерий

Aim. To estimate immunobiochemical markers of the stress response during uterine artery embolization (UAE), and to assess the connection of the endocrine and immune response with pain severity Materials and мethods: 62 patients (ages 31 to 56) with a diagnosis of multiple symptomatic uterine body fibroids were made EMA, and analgesia was achieved by intravenous injection of narcotic and non-narcotic analgesics. Immunobiochemical profile of the stress reaction was investigated (IL-1, IL-6, TNFα, IL-4, IL-10, C-reactive protein (CRP), adrenocorticotropic hormone (ACTH), cortisol, blood glucose) at four (I ONLY SEE 3-SMT) time points (baseline at 2 hours after occlusion of the uterine arteries, and 24 and 48 hours after surgery). Pain syndrome was assessed using a visual analogue scale (VAS) by means of hemodynamic profile.Results. The occlusion of the uterine arteries and ischemia myoma nodes lead to the development of the stress response, as anincrease in the serum concentration of pro-inflammatory (IL-1, IL-6, TNFα) and anti-inflammatory (IL-4, IL-10) cytokines, CRP, stress hormones (ACTH, cortisol) levels of glucose was observed. Pain of various intensity was recorded in all cases, and 18% of patients experienced marked pain (7 to 10 points on the VAS).Conclusion. The maximum increase in immunobiochemical stress markers coincides with the highest manifestations of pain. The necessity of optimization methods of analgesia when performing EMA with the use of immunobiochemical stress markers as a control reaction taking into account hemodynamic profile and VAS data was observed.Цель исследования. Оценка иммунобиохимических маркеров стресс-реакции при эмболизации маточных артерий (ЭМА), оценка связи выраженности эндокринного и иммунного ответа с выраженностью болевого синдрома.Материал и методы. Пациенткам (n = 62) в возрасте 31–56 лет с диагнозом «симптомная множественная миома тела матки» выполнена ЭМА, анальгезия достигалась внутривенным введением наркотических и ненаркотических анальгетиков. Исследован иммунобиохимический профиль стресс-реакции (IL-1, IL-6, TNFα, IL-4, IL-10, С-реактивный протеин (CRP), адренокортикотропный гормон (АКТГ), кортизол, глюкоза крови) в динамике, на четырех точках контроля (исходный уровень, через 2 ч после окклюзии маточных артерий, через 24 и 48 ч после операции). Болевой синдром оценивался по визуально-аналоговой шкале (ВАШ), с помощью гемодинамического профиля.Результаты. Окклюзия маточных артерий и ишемия в миоматозных узлах ведет к развитию стресс-реакции: увеличение концентрации в сыворотке крови провоспалительных (IL-1, IL-6, TNFα) и противовоспалительных (IL-4, IL-10) цитокинов, CRP, гормонов стресса (АКТГ, кортизола), уровня гликемии. Болевой синдром разной степени интенсивности регистрируется в 100% случаев, 18% пациенток испытывали выраженные болевые ощущения (7–10 баллов по ВАШ).Заключение. Максимальный прирост иммунобиохимических маркеров стресса совпадает по времени с максимальными проявлениями болевого синдрома. Выявлена необходимость оптимизации методов анальгезии при выполнении ЭМА с использованием в качестве контроля иммунобиохимических маркеров стресс-реакции, учитывая гемодинамический профиль и данные ВАШ

Reliability Analysis of a Load-Sharing k-out-of-n System Due to Its Components’ Failure

The reliability characteristics of a k-out-of-n:F system are studied in the case when a failure of one of the system’s components leads to increasing the load on others, resulting in their residual lifetimes decreasing. The situation is modeled with the help of changing the components and the system hazard rate function. The reliability function and other reliability characteristics are calculated. Numerical examples are considered

Queuing System with Two Types of Customers and Dynamic Change of a Priority

The use of priorities allows us to improve the quality of service of inhomogeneous customers in telecommunication networks, inventory and health-care systems. An important modern direction of research is to analyze systems in which priority of a customer can be changed during his/her stay in the system. We considered a single-server queuing system with a finite buffer, where two types of customers arrive according to a batch marked Markov arrival process. Type 1 customers have non-preemptive priority over type 2 customers. Low priority customers are able to receive high priority after the random amount of time. For each non-priority customer accepted into the buffer, a timer, which counts a random time having a phase type distribution, is switched-on. When the timer expires, the customer with some probability leaves the system unserved and with the complimentary probability gains the high priority. Such a type of queues is typical in many health-care systems, contact centers, perishable inventory, etc. We describe the behavior of the system by a multi-dimensional continuous-time Markov chain and calculate a number of the stationary performance measures of the system including the various loss probabilities as well as the distribution function of the waiting time of priority customers. The illustrative numerical examples giving insights into the system behavior are presented

Short-Term Mobile Network Traffic Forecasting Using Seasonal ARIMA and Holt-Winters Models

Fifth-generation (5G) networks require efficient radio resource management (RRM) which should dynamically adapt to the current network load and user needs. Monitoring and forecasting network performance requirements and metrics helps with this task. One of the parameters that highly influences radio resource management is the profile of user traffic generated by various 5G applications. Forecasting such mobile network profiles helps with numerous RRM tasks such as network slicing and load balancing. In this paper, we analyze a dataset from a mobile network operator in Portugal that contains information about volumes of traffic in download and upload directions in one-hour time slots. We apply two statistical models for forecasting download and upload traffic profiles, namely, seasonal autoregressive integrated moving average (SARIMA) and Holt-Winters models. We demonstrate that both models are suitable for forecasting mobile network traffic. Nevertheless, the SARIMA model is more appropriate for download traffic (e.g., MAPE [mean absolute percentage error] of 11.2% vs. 15% for Holt-Winters), while the Holt-Winters model is better suited for upload traffic (e.g., MAPE of 4.17% vs. 9.9% for SARIMA and Holt-Winters, respectively)

A Study of the Quantitative Relationship between Yield Strength and Crystal Size Distribution of Beeswax Oleogels

Beeswax and beeswax hydrocarbon-based oleogels were studied to evaluate the quantitative relationship between their yield strength and crystal size distribution. With this aim, oleogels were prepared using four different cooling regimes to obtain different crystal size distributions. The microstructure was evaluated by polarized light microscopy. The yield strength is measured by the cone penetration test. Oleogels were characterized by average grain size, microstructure entropy, grain boundary energy per unit volume, and microstructure temperature. We have provided the theoretical basis for interpreting the microstructure and evaluating the microstructure-based hardening of oleogels. It is shown that the microstructure entropy might be used to predict the yield strength of oleogels by the Hall-Petch relationship