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This paper proposes a strategy to use wind power (WP) that cannot be fully consumed at the load side for biogas digester (BD) heat augmentation to improve the utilization rate of biomass while promoting the consumption of WP, in view of the anti-peak nature of WP and the low gas production of BD at night in winter. In this paper, based on the model of rural integrated energy system (RIES) with biogas digester heating, a double-layer optimization model with minimum investment cost in the upper layer and optimal operation in the lower layer is developed. And then the Karush–Kuhn–Tucker (KKT) condition is used to convert the lower layer model into the constraints of the upper layer model, The Big-M method is used to linearize the nonlinear problem, and the model is transformed into a single-layer mixed integer linearization model. Finally, a use case of the algorithm is established and the CPLEX solver is called to solve the problem.

We propose a probabilistic approach to gauge the plausibility of a genetic link between a distal ejecta and a known impact structure, considering the only possible alternative that the distal ejecta could originate from an unknown impact site. We exemplify this approach in the case of three tektite strewn fields related to three known impact structures—the belizites, related to Pantasma (Nicaragua), the ivorites, related to Bosumtwi (Ghana), the moldavites, related to Ries (Germany), as well as on Manson crater ejecta. The computed probability for the unknown meteoritic impact is about 1% or less for these four cases studies.

Regional integrated energy system (RIES) with the close coupling of multiple energies faces various cascading failure risks in its operation, and formulating the risk-based optimal dispatch scheme is important to ensure the secure and economic operation of the RIES. Considering that the occurrence probability of each subsequent failure path caused by the initial failure in the cascading failure chain varies with the change of dispatch scheme, the cooling/heating and gas pipeline dynamics and the uncertainty of renewable energy, a risk-based distributionally robust optimal dispatch model for multiple cascading failures in a RIES is proposed. A kernel ambiguity set is constructed by using the maximum mean discrepancy between the real and reference probability distributions and the kernel mean embedding technology, which can obtain the more accurate worst-case probability distribution. Moreover, a surrogate modeling method based on piecewise convex quadratic functions is proposed to learn the mapping between the cascading failure risks and the decision variables, and the original large-scale mixed integer nonlinear programming model is transformed into a small-scale mixed integer quadratic constrained programming model for efficient solution. Finally, case study on an actual RIES demonstrates the effectiveness and advantages of the proposed method. Compared to optimal dispatch without considering the cascading failure risks, the proposed method can reduce the total failure risk cost by nearly 60%. • A RDROD model for multiple cascading failures in a RIES is presented. • A novel kernel ambiguity set based on maximum mean discrepancy is proposed. • The kernel mean embedding technique is used to map the probability distribution to RKHS. • A surrogate modeling method based on piecewise convex quadratic function is proposed. • Test results show the computational accuracy and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

With the close coupling of multiple energies (i.e., electricity, gas, cold, and heat) in a regional integrated energy system (RIES), failures in an energy subsystem can easily propagate to other energy subsystems via multi-energy coupling devices and result in cascading failures. Considering the dynamics of pipeline energy transmission and pipeline leakage failures, a novel dynamic model of analyzing the cooling/heating or gas pipeline leakage failure is proposed. Then a risk assessment model for cascading failures in a RIES is established, including the calculation of the probability and severity of cascading failure chain (CFC). A model for determining the failure probability of multi-energy coupling devices based on the device operation state is established, and a method for calculating the probability of CFC based on Bayes theorem is proposed. Considering the uncertainty and time correlation of renewable power, an ambiguity set based on the Jensen–Shannon divergence and the moment information of actual historical data is proposed, and then a distributionally robust optimization model for calculating the severity of CFC is established and solved by the column-and-constraint generation algorithm. Test results on a RIES demonstrate the high computational accuracy and efficiency of the proposed method. • A novel pipeline leakage failure model considering the pipeline leakage dynamics is proposed. • A risk assessment model for cascading failures in RIES considering the pipeline dynamics is proposed. • A method for calculating the probability of cascading failures in RIES based on Bayes theorem is proposed. • A novel ambiguity set combining JS divergence and uncertain moment is proposed to establish DRO model. • Test results show the computational accuracy and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Until as recently as a century ago, the exposure of biological systems to radiation was limited only to the natural sources. Today, however, a broad range of radiation types and doses have found a wide variety of uses and applications, so much so that it would be difficult to make a list of all the areas of human activity in which radiation is used for one purpose or another. The study of radiation effects on individuals and populations as a whole has become important only with the development of methods and sources of man-made radiation. Given that what is present in this case are physical effects on biological systems (living organisms), all these methods can be placed under the heading of biophysical influences. In the last 50 years, the effects of extremely low-frequency electromagnetic fields (ELF-EMF) have been studied with great diligence. These fields are the ones most commonly found in the human environment and they have been used in our studies in this field. The present paper provides a brief review of the literature data and our findings on the effects of ELF-EMF on various crop species using the RIES (Resonant Impulse Electromagnetic Stimulation) method, developed at the Faculty of Agriculture of the University of Novi Sad.

Four newly discovered moldavites from the East and West Gozdnica pits, SW Poland, are characterized. All specimens, including other four, reported earlier, are from Upper Miocene fluvial sediments of the Gozdnica Formation. Their weight varies between 0.529 and 1.196 g. The moldavites are bottle green in colour and have bubbles and inclusions of lechatelierite. Low degree of corrosion suggests short river transport, apparently eastward from Lusatia. [ABSTRACT FROM AUTHOR]

• A SMES model of RIES considering the pipeline dynamics is proposed. • The method of characteristics and data-driven parameter correction method are proposed to solve the PDEs. • An improved ADP method is proposed to recursively solve the SMES model. • Test results show the accuracy and efficiency of the proposed method. In the regional integrated energy system (RIES), the pipeline dynamics in cooling, heating, and gas networks make their source outputs and load demands difficult to balance in real-time. Hence the economic dispatch problem of RIES requires considering the pipeline dynamics to make the results in line with the actual situation. In this paper, the method of characteristics is proposed to solve the approximate analytical solution (AAS) of partial differential equations describing the gas pipeline dynamics, and the corrected parameters in the AAS are identified by the data-driven method. The high computational accuracy of the obtained AAS is verified by an example. Considering the stochastic fluctuation of renewable energy output and the energy storage ability of cooling, heating, and gas pipelines in a RIES, a stochastic multiple energy storage model for the stochastic economic dispatch problem of RIES considering the pipeline dynamics is established. An improved approximate dynamic programming algorithm considering the coupling of power balance among several adjacent time intervals due to the pipeline dynamics is proposed to efficiently solve the stochastic multiple energy storage model. Test results on an actual RIES, including comparison with the scenario-based method, demonstrate the correctness and efficiency of the proposed model and algorithm. [ABSTRACT FROM AUTHOR]

The UK government’s austerity cuts have negatively impacted many voluntary-sector interventions that provided support to refugees. One such intervention, the Refugee Integration and Employment Service (RIES), is discussed in this paper. The RIES was a UK Border Agency-funded integration programme for recognised refugees and operated through voluntary-sector organisations nationwide. Findings of this small, qualitative study tentatively suggest that without bespoke support such as RIES, refugees will struggle to make informedandstrategic decisions about their future education choices, restricting their ability to exercise autonomous agency. Current UK policy of counting refugees alongside other types of migrants will not cater for the specificity and multiplicity of issues faced by refugee young people. This will inhibit their opportunities and increase vulnerabilities, compounding their precarious position in UK society. [ABSTRACT FROM PUBLISHER]

The author has been marooned on a desert island and his only access to the outside world is via a coupon for seven free books from Amazon (don't ask how he will order the books). That doesn't sound too bad, except there is a catch: all seven books must be related to software engineering. What will the author do? [ABSTRACT FROM AUTHOR]

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