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In this paper, we present an analysis of effect of wrinkles on the solar sail performance. We describe different analytical, semi-analytical and numerical approaches to the calculation of general large-scale curvature of a solar sail as well as parameters of so-called wrinkled domains, and introduce the impact of such wrinkles on the thrust and torque of the solar sail. Finally, we present a model of an optically-orthotropic surface for such non-ideal sail, providing a connection with the Generalized Sail Model, and other solar sail thrust models.

The optimization of a solar sail-based orbital transfer amounts to searching for the control law that minimizes the flight time. In this context, the optimal trajectory is usually determined assuming constant solar properties. However, the total solar irradiance undergoes both long-term (solar cycles) and short-term variations, and recent analyses have shown that this may have an impact on solar sailing for missions requiring an accurate thrust modulation. In this regard, the paper discusses a strategy to overcome such an issue by suitably adjusting the thrust vector in order to track a reference, optimal, transfer trajectory. In particular, the sail propulsive acceleration magnitude is modified by means of a set of electrochromic material panels, which change their optical properties on application of a suitable electric voltage. The proposed control law is validated with a set of numerical simulations that involve a classical Earth-Mars, orbit-to-orbit, heliocentric transfer.

Ballistic design of solar sailing missions in the solar system is composed of defining the design parameters, the control programs, and the trajectories that provide performance goals of a flight. The use of a solar sail spacecraft imposes specific restrictions on mission parameters that include the degradation limit on the flight duration, the maximum temperature of solar sail's surface, the minimum distance from the Sun, the maximum angular velocity of the spacecraft's rotation and others. Many authors considered the impact of these restrictions on the design of the mission separately, but they used a sophisticated method of finding the exact optimal motion control or applied the most straightforward laws of motion control. This paper uses local-optimal control laws at the complete mathematical models of motion and functioning of solar sail spacecraft to describe a technique of designing interplanetary missions. The described method avoids the need to obtain an accurate optimal solution to the control problem and does not cause significant computational difficulties.

The interaction between electromagnetic waves and matter is the working principle of a photon-propelled spacecraft, which extracts momentum from the solar radiation to obtain a propulsive acceleration. An example is offered by solar sails, which use a thin membrane to reflect the impinging photons. The solar radiation momentum may actually be transferred to matter by means of various optical phenomena, such as absorption, emission, or refraction. This paper deals with the novel concept of a refractive sail, through which the Sun’s light is refracted by crossing a film made of polymeric micro-prisms. The main feature of a refractive sail is to give a large transverse component of thrust even when the sail nominal plane is orthogonal to the Sun-spacecraft line. Starting from the recent literature results, this paper proposes a semi-analytical thrust model that estimates the characteristics of the propulsive acceleration vector as a function of the sail attitude angles. Such a mathematical model is then used to analyze a simplified Earth-Mars and Earth-Venus interplanetary transfer within an optimal framework.

The LightSail 2 mission is the culmination of a decade-long program sponsored by The Planetary Society to advance solar sailing technology. The objective of LightSail 2 is to demonstrate controlled solar sailing in Earth orbit using a CubeSat platform. The LightSail 2 attitude is controlled using a single-axis momentum wheel and magnetic torque rods. During solar sailing operations, two 90 degree slews are performed each orbit to harness momentum from solar photons. Flight data show that LightSail 2 is successfully controlling its orientation relative to the Sun, and the controlled thrust from solar radiation pressure is measurably reducing the rate of orbital decay. The Planetary Society declared LightSail 2 mission success on July 31, 2019. This paper provides an overview of the LightSail 2 mission implementation, including the design of the flight system and flight software, and the pre-launch testing program. A summary of LightSail 2 mission operations is provided, including a description of the ground system. Solar sailing performance is presented, and anomalies encountered during the mission are discussed. The flight team continues to refine solar sailing performance and conduct on-orbit imaging for engineering purposes and to engage public interest. The LightSail program is entirely donor-funded, with over 50,000 contributors around the globe.

This paper reports on the manufacturing and evaluation of a solar power sail membrane prototype for the OKEANOS project. The in-house prototype was built by the Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency. Mechanical and electrical evaluation tests were conducted. The membrane, thin-film solar cells, reflectivity control devices were good condition after the manufacturing and handling. The improvements in the manufacturing process and design were found. The manufacturing process and design were fundamentally established. After the prototype, improvement plans for the manufacturing process and design were tried. We have a prospect of manufacturing the flight model sail and continue to the development.

We present a detailed mechanical and thermal analysis of a stand-alone nanospacecraft that performs asteroid flybys in the main asteroid belt (2.75 AU) and one Earth flyby at the end of the mission to return the gathered data. A fleet of such nanospacecraft ( 10 kg) has been proposed as part of the Multi-Asteroid Touring mission concept, a nearly propellantless mission where the electric solar wind sail (E-sail) is used for primary propulsion. The fleet makes flybys of thus far poorly characterised asteroid populations in the main belt and downlinks scientific data during the returning Earth flyby. The spacecraft size is close to a three-unit cubesat with a mass of less than 6 kg. The spacecraft is designed for a 3.2-year round trip. A 20-km-long E-sail tether is used. A remote unit is attached to the tether’s tip and stowed inside the spacecraft before the E-sail commissioning. The remote unit is slightly smaller than a one-unit cubesat with a mass of approximately 750 g. With an electrospray thruster, it provides angular momentum during tether deployment and spin-rate management while operating the E-sail. The selection of materials and configurations is optimised for thermal environment as well as to minimise the mass budget. This paper analyses the main spacecraft and remote-unit architectures along with deployment and operation strategies from a structural point of view, and thermal analysis for both bodies.

Asteroid mining has the potential to greatly reduce the cost of in-space manufacturing, production of propellant for space transportation and consumables for crewed spacecraft, compared to launching the required resources from the Earth’s deep gravity well. This paper discusses the top-level mission architecture and trajectory design for these resource-return missions, comparing high-thrust trajectories with continuous low-thrust solar-sail trajectories. The paper focuses on maximizing the economic Net Present Value, which takes the time-cost of finance into account and therefore balances the returned resource mass and mission duration. The different propulsion methods are compared in terms of maximum economic return and sets of attainable target asteroids. Results for transporting resources to geostationary orbit show that the orbital parameter hyperspace of suitable target asteroids is considerably larger for solar sails, allowing for more flexibility in selecting potential target asteroids. Also, results show that the Net Present Value that can be realized is larger when employing solar sailing instead of chemical propulsion. In addition, it is demonstrated that a higher Net Present Value can be realized when transporting volatiles to the Lunar Gateway instead of geostationary orbit. The paper provides one more step towards making commercial asteroid mining an economically viable reality by integrating trajectory design, propulsion technology and economic modelling.

This paper proposes a novel finite element Kalman filter to estimate the unmeasurable state of space tether systems based on the measured state at its ends only. The finite element method calculates the unmeasurable internal state as the virtual measurement based on the dynamic model of the system by imposing the input of measured state at the boundary to the model using the Lagrange multiplier method in the spatial space. Combining the real and virtual measurement into a hybrid measurement model of the system, the full state is reconstructed and propagated in the temporal space by the extended Kalman filter. Two state-space system models, the dynamics-based and kinematics-based state models, in the Kalman filter are explored. The observability and stability of the newly proposed finite element Kalman filter are examined and proved. The advantages of the proposed state estimator are (i) the singularity in the virtual measurement of state caused by the number of internal state greater than the number of state measured at the boundary is eliminated in the statistic meaning by the Kalman filter, and (ii) the effects of noises of the observation data and the uncertainties of model discretization are considered and minimized. The correctness and effectiveness of the proposed state estimator is demonstrated by the numerical analysis of a space tether system orbiting around the Earth. The results show the proposed state estimator with only measured state at the ends of the tether successfully provides an accurate time history estimation of geometric configuration and motion of the entire tether. Moreover, the results also show the difference caused by the dynamics-based and kinematics-based system models in the state estimator is negligible. The kinematics-based system model should be used in the state estimator due to its significantly low computational load. Finally, the proposed method can be easily applied for the state estimation process for other space tethered spacecraft systems.

This paper provided a design of bat-inspired tailless flapping wing unmanned aerial vehicle (UAV) based on the biological data of the large flying fox. The wing span of the UAV is 1.68 m and the total mass is 289 g. Aerodynamic characteristics at design cruise speed were analyzed based on the computational fluid dynamics (CFD) method. Selected variables within the analysis are angle of attack and flapping frequency. Prototype of the UAV has been manufactured follows the design parameters. The flapping mechanism employed a 2-DOFs revolute-spherical-spherical-revolute (RSSR) system to reflect the flapping attitude of bats. An outdoor test flight was then processed with the manufactured prototype. Onboard flight data recorder (FDR) was equipped to conserve the flight data such as flight speed, pitching angle and the three-dimensional position of the flight. It is shown by the data obtained from the FDR that the bat-inspired UAV is able to achieve the stable cruise with circular route at flight speed 6.8 m/s with the average angle of attack 4.1 degrees and flapping frequency 3.7 Hz. Test flight shows that the UAV is able to provide a 5 minutes free outdoor cruise with the equipped Li-Po battery. Research proves that the tailless configuration flapping wing UAV is able to sustain a stable flight, which provides a new design possibility for future researches.

This paper addresses the attitude stabilization problem with the optimization objective regarding system performance and energy consumption for rigid spacecraft. Novel state-dependent coefficient (SDC) parameterizations are developed to reduce the optimization problem to solving the state-dependent Riccati equation (SDRE). To be explicit, a proper SDC parameterization is selected for the stabilization mission among infinite feasible SDC representations by utilizing an improved guideline. Subsequently, a novel analytical SDC reconstruction is evoked alternatively at the mission breakdown region in which the derived SDC parameterization fails to operate. Behind the scenes, the anti-unwinding behavior is supported by the explicit sampling SDC forms derived for the scalar part of the unit quaternion. The novelty of two developed SDC parameterizations lies in that they not only render the maximal pointwise controllable space to facilitate the control mission, but also cover the whole maneuvering domain without any breakdowns. Moreover, the computational burdens for online SDRE solvability checking and numerical SDC reconstruction are alleviated significantly. Finally, comparative numerical simulations are implemented to highlight the superior performance of the presented scheme.

This paper addresses the feasibility analysis of a re-entry flight strategy from low Earth orbit, developed for an innovative re-usable wing-body concept, having a rather high surface-to-mass ratio. The re-entry procedure envisages a longer and gradual dissipation of vehicle's total energy, carried out at a flight path angle lower than typical Shuttle-like values. Hence, the heat flux is kept constant at a predicted threshold, thus allowing the radiative cooling of the spacecraft heatshield at a suitable temperature. The selected flight approach relies on a prescribed guidance law which modulates the glider angle of attack as function of Mach number, to assure the desired convective heat flux level for a certain time. Based on a low-flight path assumption, analytical considerations are derived to evaluate geometric, aerodynamic, and flight parameters that influence the convective heat flux. Furthermore, candidate guidance laws are determined formulating an optimization-based heat flux targeting procedure. The relevance of aerodynamic performances is also underlined, provided that, by results high lift configurations dictate lower angles of attack and vice versa. Analytical and numerical results evidence existing relation between surface-to-mass ratio, lift-to-drag ratio and flight duration time, that can be used “on design” to modulate the aerothermal loading. The current approach is suitable to explore less challenging aerothermal environments in order to improve reliability and affordability of space operations in the near Earth space.

As we know, choice of coordinates is of great significance for the performance of analytical and computational approaches in astrodynamics. In this paper, we consider the application of a set of vectorial orbital elements of the Milankovitch type to low-thrust Earth-orbit trajectory optimization and develop a methodology to rapidly work out optimal solutions of low-thrust Earth-orbit transfers. A new vectorial dynamic model of a thrusting spacecraft are presented, and the model is concise and nonsingular for any non-degenerate orbits. A parameter estimation approach is introduced to solve the complex two-point boundary value problem by setting the unknown values of the initial co-states as parameters to be estimated and the boundary values as desired observations. The performance of the proposed dynamic model is demonstrated by optimizing two orbit-raising trajectories and one orbit-lowering trajectory. The simulation results indicate that the proposed dynamic model can give the optimal solutions of low- thrust Earth-orbit transfers with efficiency and robustness.

This paper presents the design and fabrication details of a small-scale testing system for characterizing a novel nose landing gear shimmy damper. This test rig is designed to simulate take-off and landing conditions of an aircraft nose landing gear in the laboratory environment. A roller drum is employed to simulate the forward speed of the aircraft on the ground, while an impact hammer mechanism is used to induce shimmy through a small initial tire slip. Weights can be used to induce vertical force exerted by the fuselage. The vibration signals are recorded using accelerometers, and processed numerically to obtain shimmy characteristics. A prototype of the novel shimmy damper designated as the Symmetric Torque Link Damper (STLD) is fabricated. The specifications of STLD are discussed in previous publications and summarized in the current paper. The experimental results including rotational vibration time histories, peak frequencies, and attenuation characteristics for the STLD are presented and compared with those of the baseline system without a shimmy damper, as well as with the built-in shimmy damper trends. Overall, this experimental work confirms the stability gain offered by the STLD, while it does not outperform the built-in damper in all scenarios. Instead, STLD has the attractive features of being retrofittable to existing landing gears and is symmetric in design, leading to an even distribution of dynamics loads on the gear. Furthermore, the testing apparatus presented in this work contributes to shimmy mitigation practice by offering a novel, yet simple, validation approach suitable for early prototype developments.

This paper studies a shortest-time dissipation trajectory of a tumbling target after being captured by a space manipulator. A time-optimal control problem (OCP) that considers target attitude motion bounds as well as interaction torque limits at the grasping point is formulated. Then, the state and input inequality constraints are represented as extended dynamical sub-systems and saturation functions, respectively. Thereby, the OCP can be solved using the Calculus of Variations method with a highly accurate solution. Additionally, a coordinated controller using reference accelerations is proposed for the space manipulator, which guarantees that both the target and base spacecraft of the space manipulator can track desired trajectories. Numerical simulations demonstrate the effectiveness of the proposed method.

This paper investigates the robust tracking control problem for spacecraft attitude maneuvering with prescribed performance. Firstly, a control scheme is studied based on a quasi-sliding-mode approach which can simultaneously restrict the convergence speed and the steady-state error of both Euler angle and relative angular velocity. Then, to reduce actuators' energy consumption, a three-layer back-propagation neural network is combined with the above control law to auto-tune the control gains. Finally, the performance and effectiveness of the control approach are demonstrated by numerical simulation.

In this paper, a low-voltage, low-power, ultra-wideband, and improved linear up-conversion folded mixer with a coverage range of 1.5–7 GHz is presented. The mixer is designed with 0.18 μm CMOS technology. The folded method is adopted to reduce the supply voltage as well as the DC power consumption. The linearity of the mixer is enhanced using the multiple-gate transistor (MGTR) topology. The transconductance stage is designed with transistors of different sizes, namely, a main transistor and an auxiliary transistor. The gate voltage of the auxiliary transistor is adjusted to change the distortion coefficient such that the nonlinearity of the main transistor is compensated. The up-conversion mixer can achieve a measured conversion gain of 7.2–11.2 dB. The third-order input-intercept point (IIP3) is –6 to –3.5 dBm, and the DC power consumption is 5.8 mW for a supply voltage of 1 V. The measured LO-to-IF and LO-to-RF port-to-port isolations are 37–53 dB and 30–39 dB, respectively. The measured IF-to-RF port-to-port isolation is 36–60 dB. The chip size of the up-conversion mixer, including the pad frames, is 1.32 mm2.

Traditionally, analogue filter designers synthesise their circuit topologies using pencil-and-paper method. Based on their previous experience, they generally use their intuition to reach proper network configuration for the desired filter function. However, this approach might be very time-consuming and cumbersome. With the advent of computer technology, the generation of analogue filters (or any other types of circuit for that matter) can be done using software. Taking advantage of this high computing power, some evolutionary methods, like genetic algorithms (GAs), can be employed to obtain the desired circuits sophistically, which generally leads reaching the goal faster. In this paper, automatic synthesis of filters utilizing GAs is presented. Although the approach can be applied to all analogue filters, this paper specifically focuses on active-RC filter topologies, which compose of an active element, e.g. operational amplifier, and resistors and capacitors. Some of the filter topologies that are generated by the constructed software are presented. Experimental results regarding to GA performance are also included.

In this paper, the performance of inverter and ring oscillator circuits based on the nanoscale double-gate (DG) FET is improved by using device engineering approaches. The modification of the parameters affecting the intrinsic delay time of the DGFET, such as on-current and the total gate capacitance can be improved the oscillation frequency of the ring oscillator. Accordingly, the effects of gate oxide thickness ( t ox ) and body thickness ( t body ) on the electrical characteristics of the device and circuit-level have been investigated so that we could provide a design of ring oscillator with improved oscillation frequency. Moreover, the enhanced source doping concentration and graded-channel (GC) techniques have been applied and analyzed at the device-level to ameliorate the oscillation frequency of the ring oscillator. Finally, we have presented the graded-channel (GC) strategy with two types of high-low (HL) and low-high (LH). The extracted results illustrate that the total gate capacitance of the LH-GC-DGFET is improved significantly compared to the HL-GC-DGFET. Consequently, the efficient design of the ring oscillator based on LH-GC-DGFET with superior oscillation frequency is proposed. The TCAD mixed-mode simulation has been used for simulating the circuits.

Non-orthogonal multiple access (NOMA) is an emerging multiple access technique to provide higher spectral efficiency and data rates for future wireless communications. In this paper, outage probability expressions are obtained for NOMA over κ - μ shadowed faded channel, which can be applied to analyze the performance in mobile, satellite and underwater communication. Initially we observed the signal to interference ratio (SIR) at user equipment (UE) by considering the inter and intra cellular interference. The outage probability expressions are obtained for NOMA with maximum ratio and selection combining. In this paper, we also calculated the outage results with random number of interferers. The analytical results are presented for two users which are at near and edge positions of a Voronoi cell. Finally, simulated results are presented to validate the analytical expressions.

In this paper, the gradient elliptical slots (ES) are designed to enhance the operating bandwidth of the Vivaldi antenna (VA) in the relatively low frequency band. The antenna EVA is implemented by integrating the elliptical slots to the edge of the VA, which extends the low frequency operating point from 7.4 GHz to 5.4 GHz while obtaining the miniaturized design of the antenna. To address the problem of the gain deterioration, we design ultra-wideband metasurface lens (ML) and integrate it into the aperture of the EVA. The lens has a simple structure that can perform dual polarization modulation on electromagnetic waves. The propagation path of the electric field at the aperture of the EVA loaded with the ML is extended, and the electric field behaves more planar. We simulate and analyze the conventional VA, EVA, and ML integrated EVA (MLEVA). The VA and the proposed MLEVA are fabricated and measured. The results match those of the simulations. The operating bandwidth of the proposed antenna is 5.4–18 GHz that has been expanded compared with the VA. And the gain has increased by approximately 0.3–3.2 dB without changing the overall antenna sizes. The sidelobe level is significantly reduced at the same time. Generally, miniaturization and performance enhancement of the VA is achieved in the proposed MLEVA.

In this paper, a high-gain and wideband circular polarization (CP) patch antenna using reflective focusing metasurface was proposed and demonstrated. The initial design of patch antenna is made of a slot planar patch radiation part fed by coplanar waveguide (CPW). The simulated return loss below −10 dB of the initial design is from 6.2 to 13.8 GHz with the relative bandwidth of 76%, and the average gain is only about 4.5 dBi. In addition, the simulated 3-dB axial ratio bandwidth (ARBW) of the initial design is 78.7% from 6 to 13.8 GHz. The antenna structure was modified to enhance the gain and radiation performance by adding the reflective focusing geometric metasurface. The metasurface with wideband high efficiency cross-polarization reflection, is arranged to construct the phase gradient paraboloid for energy gathering. Simulation results indicated that the antenna combined with reflective focusing metasurface achieves an effective wideband impedance bandwidth (return loss

This paper provides evidence to support that riluzole, an FDA-approved treatment for amyotrophic lateral sclerosis (ALS), like many neuroprotective agents, displays and exerts hormetic biphasic dose responses. These findings have important implications for the experimental study and clinical treatment of ALS.

Understanding the motivations, intentions, and capabilities of terror organizations is highly important to understanding and assessing the risk they present, and to implement effective counter-terror measures. Currently, research of terror organizations consists of designated areas such as economy, security, cyber, and media. Despite ample research on the psychology of the individual terrorist, research regarding the terror organization as a group entity is scarce. The present paper thus presents an exploratory typology, based on both individual and group psychology, which is designed to provide a psychological assessment of terror organizations. Applying a deductive thematic analysis approach, the profiles of three terror organizations: Hezbollah, Hamas, and IS, were analyzed using a five-dimension typology. The data relating to the three organizations was based on two main sources. First, academic journals and official releases by Non-Governmental Organizations (NGOs), and second, official publications in Arabic by the organizations themselves. Results show different profiles for the three organizations in terms of their psychological maturity. We propose that different approaches to countering terrorism may be considered based on each organization's unique profile.

This systematic review aimed to explore the research papers related to how Internet and social media may, or may not, constitute an opportunity to online hate speech. 67 studies out of 2389 papers found in the searches, were eligible for analysis. We included articles that addressed online hate speech or cyberhate between 2015 and 2019. Meta-analysis could not be conducted due to the broad diversity of studies and measure units. The reviewed studies provided exploratory data about the Internet and social media as a space for online hate speech, types of cyberhate, terrorism as online hate trigger, online hate expressions and most common methods to assess online hate speech. As a general consensus on what is cyberhate, this is conceptualized as the use of violent, aggressive or offensive language, focused on a specific group of people who share a common property, which can be religion, race, gender or sex or political affiliation through the use of Internet and Social Networks, based on a power imbalance, which can be carried out repeatedly, systematically and uncontrollably, through digital media and often motivated by ideologies.

A significant problem for industrial management has always been the frequency of workplace fatalities and injuries. From production plants to offices to construction sites and beyond, every workplace has safety threats and hazards. To recognize certain objects, circumstances, practices, etc., that can cause harm, especially to individuals, a detailed look at the workplace becomes crucial. It is important to evaluate and determine how severe and likely the danger is after identification is made. The range of cumulative challenges, partially linked to technology developments with rising expectations, has to be broadly considered. Currently, it needs systematic risk estimation, enhancement of past lessons in learning, and the concept of appropriate data processing techniques to be combined with adequate capacity to cope with unforeseen events and provide the right support to enable risk management. Therefore, this paper suggests a risk management methodology focused on artificial intelligence (AI). A Deep Neural Network for Workplace Risk Estimation (DNN-WRE) model is explicitly generated and trained to predict the working environment's risks. The DNN-WRE is evaluated by a common risk prediction seen in the workplace, i.e., Musculoskeletal Disorders (MDs). Furthermore, this paper re-tuned the transfer learning network ResNet 18 to predict MDs. The training and validation of the proposed DNN-WRE have been observed with the highest prediction accuracy of 93.86% compared with the pre-trained ResNet 18 model.

CONTEXT A concept was presented to produce N fertilizer by digesting straw in a biogas plant and transporting bio-methane to a fertilizer plant through a gas grid substituting natural gas. OBJECTIVE The rational was to find out if straw, a residue not infringing on food production and not needing extra cropland, converted to methane in a biogas reactor, is a viable option for ammonia synthesis. METHODS Scenarios calculations were based on straw from 1 ha wheat producing 7 Mg of grain using 150 kg of fertilizer N. Removal rates of straw were 60 or 100%. Digestion residues were returned to fields within a radius of 50 km. Three scenarios with varying straw removal and low to high efficiency of the biogas and fertilizer plant were assessed. RESULTS AND CONCLUSIONS A sensitivity analysis showed the combination of a medium to high efficient biogas and fertilizer plant using between 3.5 and 7 Mg straw covered the energy need for crop management, transportation of straw and digestate and N fertilizer production and still delivered a surplus of 838–9192 kWha ha−1. The amount of 1 Mg of straw enabled the production of 94 to 173 kg fertilizer N. SIGNIFICANCE Use of straw can be a useful alternative for N fertilizer production making agriculture more sustainable.

CONTEXT Public and private research institutions are grappling with the challenges and opportunities of embedding dimensions of responsible innovation within their research and development programs, including those seeking to transform agricultural productivity and sustainability through digital technologies. Central to meeting this challenge is building institutional, organisational and professional capacity for anticipation and reflexiveness within multidisciplinary research communities. Foresighting methodologies provide a means by which this might be usefully and practically enabled, whilst also shedding light on the broader social and ethical implications of alternative agricultural technology development pathways under uncertain environmental and industry futures. OBJECTIVE This paper presents the results of a participatory foresighting exercise undertaken as part of a large, publicly funded multi-disciplinary research initiative designed to build a common big data infrastructure to harness the benefits of the digital revolution for the Australian agricultural and land sectors. We seek to explore what role digital technology will play in the future of Australian agriculture and to consider the social and ethical implications. METHODS We ran a one-day foresighting workshop comprised of four steps – 1) horizon scanning to identify trends 2) selecting two drivers of change 3) producing a matrix to generate scenarios 4) building and refining scenarios. Participants explored different possible futures of farming in Australia, with a focus on scenarios involving socio-technical dimensions of digital agriculture to consider the implications of these futures for research practice and for farming communities. RESULTS AND CONCLUSIONS Four scenarios were developed, distinguished by the interplay of two critical but uncertain drivers of change identified by participants, namely: the degree of resource security or insecurity that future agricultural enterprises are likely to experience; and the degree to which farming sectors maintain traditional farm business models and associated value chains or transition to more diverse or innovative business models. The process highlighted the need to increase the capacity and opportunity for more reflexivity in research and development, if positive outcomes were to be achieved. SIGNIFICANCE The scenarios we produced provide a catalyst for conversation about the implications of digital technology development in Australia and globally, for industry, policy and research and development. In particular, the scenarios highlight potential changes in farm business models, decision making, and beneficiaries and inequities of new technologies and other components of food value chains. The paper also serves as a guide and prompt for others, by demonstrating one way reflexivity can be achieved in organisations attempting innovation.

CONTEXT The COVID-19 pandemic has resulted in immediate and wide impacts on human and agricultural systems. While some of the positive and negative impacts of COVID-19 on the environment and economies are emerging, there is not a comprehensive understanding of the potential impacts of COVID-19 on the most vulnerable farmers. OBJECTIVE The purpose of this study is to evaluate the immediate impacts of COVID-19 on agricultural and food systems in the United States. Our aim is to quantify the impacts on labor productivity in crops and livestock production considering the heterogenous vulnerability of different farmworkers. We are interested in measuring the production that is not realized due to COVID-19. METHODS In this paper, we introduce IMLAP, Immediate impact Model of Local Agricultural Production. This model is an economic framework considering short-term agricultural production responses to economic, environmental, and policy changes. We investigate the potential impacts of COVID-19 on the farmers in the U.S. for each county with a special focus on female, Hispanic, black and African American, and small-scale producers. RESULTS AND CONCLUSIONS Considering the impacts of COVID-19 on labor, the findings of this study suggest a decline in agricultural output in all the U.S. counties ranging from 1.18% to 7.14% of total production. Our simulation results show that counties with a higher number of small-scale farms, non-white farmers, and female-operated farms are the most vulnerable to COVID-19. Also, we argue that the stimulus policies and support packages must target these communities of producers to ensure that their livelihood is protected. The findings suggest that productivity growth (technological improvements) and international trade can eliminate the negative impacts of pandemics. SIGNIFICANCE The proposed quantitative framework of this study is a simple yet novel model that empowers diverse research communities to provide a quick analysis of the impacts of unprecedented events. It offers a holistic framework to evaluate the response of agricultural production to changes in availability and productivity of labor, machinery & equipment, land, fertilizer, seeds, and other inputs. This study presents new foundations for agricultural research communities to provide solutions to agricultural resilience challenges and highlights the significance of demand drivers, technological growth, and international trade in strengthening the food system.

Context Resilience represents the ability of systems to anticipate, withstand, or adapt to challenges. Times of great stress and disturbance offer opportunity to identify and confirm key contributors to agri-food system resilience. The COVID-19 pandemic and its related consequences constituted major shock, challenging the resilience of many agri-food systems worldwide. Objective This paper aimed to report the immediate effects of the COVID-19 crisis on various key actors from Flemish food supply chains. By analysing and assessing the observed impacts of and reactions to this crisis from a resilience perspective, it also aimed to gain empirical evidence on resilience-enhancing characteristics of agri-food systems to sudden shocks. Methods A first, quantitative step of our mixed method approach measured 718 farmers' experienced impacts and applied strategies following the crisis through an online survey. A second, qualitative step captured impacts and responses from other key actors downstream the food supply chain through 22 in-depth interviews and 18 on-line questionnaires. Data gathering and interpretation followed a conceptual framework for analysing resilience of agri-food systems to external challenges, that we developed based on the literature. The framework states that resilience actions stem from three types of resilience capacities: anticipatory, coping and responsive capacities. These are determined by both resources allocated by system actors, as well as by resilience attributes from the system. Results and conclusions The COVID-19 crisis induced a simultaneous dropped demand for food products in the hospitality industry and risen demand in retail. This shifted demand significantly disturbed food production, processing and marketing processes in terms of labour organization, planning, operation, logistics, and economic returns. Perceived impacts varied extensively across actors from the agri-food system, mostly depending on their marketing strategy, customer base, and flexibility and diversity of their practices. Reported reactions to this crisis revealed that resilience capacities varied according to actors' abilities to negotiate prices, adjust production processes, and maintain or reorient sales. Some agri-food sectors showed higher responsive capacity because of a higher connectivity and self-organization within the system. Significance Our findings suggest that flexibility and diversity, despite their tendency to diminish price optimums, increase resilience capacities, which may be more beneficial to systems for thriving in turbulent and uncertain environments. A more tangible, operationalized understanding of resilience is necessary to effectively improve agri-food system resilience. Our conceptual framework proved a valuable tool for operationalizing resilience assessments to major shocks.

Increasing agricultural productivity through irrigation technologies is recognized as an effective way to improve smallholders’ livelihoods and food security in developing countries. However, most smallholder farmers do not have access to irrigation technologies. Using a double-bounded contingent valuation survey data from smallholders in Ethiopia and probit and bivariate probit models, this paper analyzes smallholder farmers’ demand for agricultural water lifting technologies (WLTs) and the factors affecting the demand for these technologies. Assessment of farmers’ preferences among three water lifting technologies available in local markets (motorized pump, rope and washer and pulley) show that farmers prefer motorized pumps to pulley or rope and washer technologies. Use of motorized pumps is more efficient and save labour than pulley or rope and washer technologies. However, results show that smallholders are constrained by inadequate access to financing options to adopt more efficient and labour-saving water lifting technology and hence operate below the production possibility frontier. Enhanced access to finance could help ease this constraint and allow smallholders to acquire more efficient irrigation technologies, enhance adoption and improve productivity. With a growing population pressure and land fragmentation in rural Ethiopia, the livelihoods of smallholders depend mainly on the meagre land endowment they possess. Increasing the productivity of land using yield enhancing technologies, particularly multiple cropping per year via small-scale irrigation is key to improve their livelihoods. Targeted interventions are thus warranted to mitigate the key adoption constraints such as improving access to credit and technical know-how of smallholders.

The use of reclaimed or treated water from urban wastewater treatment plants for irrigation has been proposed as an alternative water source to address water scarcity issues in Europe. In this paper using agro-economic modelling, we analyse if treated water available for agriculture has the potential to reduce freshwater abstraction and, consequently, water stress. Implementing exogenous treated water quantities as an additional water supply at NUTS 2 level in the CAPRI model, we found that treated water reuse is a possible alternative supply source to address water shortages with a very negligible effect on farmers’ income and food production in the EU. However, the actual water reuse and water stress reduction is very limited due to high costs. Even climate change effects on water availability and precipitation failed to induce higher use. The one-size-fits-all approach modelled via a flat rate water price only encourages the reuse of treated water in a limited number of EU member states. Thus, in order to maximise the potential of reused water to address water scarcity, different rates should be used so as to ensure higher treated water volumes at lower costs., Highlights • Water reuse is a possible alternative supply source to address water shortages. • Negligible effect on farmer's income and food production in EU. • Actual water reuse and water stress reduction is very limited. • Financial incentives in form of subsidies necessary to improve water reuse for irrigation.

In this paper, two models for classification of microalgae species based on artificial neural networks have been developed and validated. The models work in combination with FlowCAM, a device capable of capturing each of the particles detected in a sample and obtaining a set of descriptive features for each one. One of the models uses these feature variables as input, while the other makes use of the captured images, both being able to distinguish between two well-known species of microalgae, Scenedesmus almeriensis and Chlorella vulgaris, calculating the proportion of each of these in the analyzed mixture. The models were trained with pure samples of each specie and validated using mixed combinations of them. The results confirm the potential of image analysis and deep learning techniques for the identification of microalgae cultures, as well as the higher accuracy of the feature-based model, thus extending the range of classification approaches in this field.

The development of coronavirus disease 2019 vaccines in the current and planned clinical trials is essential for the success of a public health response. This paper focuses on how physicians should implement the results of these clinical trials when counseling patients who are pregnant, planning to become pregnant, breastfeeding or planning to breastfeed about vaccines with government authorization for clinical use. Determining the most effective approach to counsel patients about coronavirus disease 2019 vaccination is challenging. We address the professionally responsible counseling of 3 groups of patients-those who are pregnant, those planning to become pregnant, and those breastfeeding or planning to breastfeed. We begin with an evidence-based account of the following 5 major challenges: the limited evidence base, the documented increased risk for severe disease among pregnant coronavirus disease 2019-infected patients, conflicting guidance from government agencies and professional associations, false information about coronavirus disease 2019 vaccines, and maternal mistrust and vaccine hesitancy. We subsequently provide evidence-based, ethically justified, practical guidance for meeting these challenges in the professionally responsible counseling of patients about coronavirus disease 2019 vaccination. To guide the professionally responsible counseling of patients who are pregnant, planning to become pregnant, and breastfeeding or planning to breastfeed, we explain how obstetrician-gynecologists should evaluate the current clinical information, why a recommendation of coronavirus disease 2019 vaccination should be made, and how this assessment should be presented to patients during the informed consent process with the goal of empowering them to make informed decisions. We also present a proactive account of how to respond when patients refuse the recommended vaccination, including the elements of the legal obligation of informed refusal and the ethical obligation to ask patients to reconsider. During this process, the physician should be alert to vaccine hesitancy, ask patients to express their hesitation and reasons for it, and respectfully address them. In contrast to the conflicting guidance from government agencies and professional associations, evidence-based professional ethics in obstetrics and gynecology provides unequivocal and clear guidance: Physicians should recommend coronavirus disease 2019 vaccination to patients who are pregnant, planning to become pregnant, and breastfeeding or planning to breastfeed. To prevent widening of the health inequities, build trust in the health benefits of vaccination, and encourage coronavirus disease 2019 vaccine and treatment uptake, in addition to recommending coronavirus disease 2019 vaccinations, physicians should engage with communities to tailor strategies to overcome mistrust and deliver evidence-based information, robust educational campaigns, and novel approaches to immunization.

Objective The purpose of this paper is to review the literature and compile key clinically relevant applications of telemedicine for use in otolaryngology relevant to the post-COVID-19 era. Study design Systematic Literature Review. Data sources Pubmed and Google Scholar. Review methods Pubmed and Google Scholar were queried using combined key words such as “telemedicine,” “covid” and “otolaryngology.” The searches were completed in March–August 2020. Additional queries were made with particular subspecialty phrases such as “rhinology” or “otology” to maximize yield of relevant titles. Relevant articles were selected for abstract review. Applicable abstracts were then selected for review of the full text. Results Initial search identified 279 results. These were screened for relevance and 100 abstracts were selected for review. Abstracts were excluded if they were not in English, not related to otolaryngology, or if the full text was unavailable for access. Of these, 37 articles were selected for complete review of the full text. Conclusion The sudden healthcare closures during the COVID-19 pandemic resulted in a sharp increase in the use of telemedicine, particularly in subspecialty fields. Otolaryngologists are at a unique risk of infection resulting from the examination of the head and neck and aerosol-generating procedures due to the predilection of viral particles for the nasal cavities and pharynx. The COVID-19 pandemic may have served as a catalyst to implement telemedicine into clinical practice, however identifying ways to integrate telemedicine long term is key for a sustainable and viable practice in the post-COVID-19 era. Although many states are now finding themselves on the down-sloping side of their infection rate curve, many others remain at the apex. Additionally, the risk of future waves of this pandemic, or the onset of another pandemic, should not be overlooked. Practice modification guidelines that mitigate infection risk by utilizing telemedicine would be useful in these instances. Telemedicine can help to reduce infection spread by limiting unnecessary in-person interactions and help conserve personal protective equipment (PPE) by facilitating remote care with the added benefits of expanding care to broad geographic areas, limiting cost, time, and travel burden on patients and families, and enabling consistent follow up.

Background Extracellular matrix molecules (ECMM) expression during tertiary dentinogenesis provides useful information for regenerative applications and efficacy of pulp capping materials. Aim To identify and review the expression and roles of non-collagenous ECMM after successful direct pulp capping (DPC), following mechanical pulp exposures, via immunohistochemistry (IHC). The study addressed the question of where will successful DPC impact the IHC expression of these molecules. Data sources In vivo animal and human original clinical studies reporting on ECMM in relation to different follow-up periods were screened and evaluated via descriptive analysis. The electronic literature search was carried out in three databases (MEDLINE/PubMed, Web of Science, Scopus), followed by manual screening of relevant journals and cross-referencing, up to December 2018. Study eligibility criteria, participants, and interventions Randomized and non-randomized controlled trials, conducted in humans and animals, were selected. Histological evidence for tertiary dentine formation was a prerequisite for IHC evaluation. Study appraisal and synthesis methods The methodological quality of the included articles was independently assessed using the Systematic Review Centre for Laboratory animal Experimentation (SYRCLE) and the Cochrane risk of bias tool (RoB 1), respectively. Results From a total of 1534 identified studies, 18 were included. Thirteen papers evaluated animal subjects and five studies were carried out on humans. In animals and humans, fibronectin and tenascin expressions were detected in pulp and odontoblast-like cells (OLC); dentine sialoprotein was expressed in both soft and newly-formed mineralized tissue. In animals, bone sialoprotein was early expressed, in association with OLC and predentin; the immunoreactivity for dentine sialophosphoprotein and dentine matrix protein-1 was associated with the OLC and dentine bridge; osteopontin was expressed in OLC, predentine and reparative dentine. A considerable heterogeneity was found in the methodologies of the included studies, as well as interspecies variability of results in terms of time. Conclusions and implications of key findings Within the limited scientific evidence, all non-collagenous ECMM expressions during tertiary dentinogenesis are active and related to soft and hard tissues. There is a shortage of human studies, and future research directions should focus more on them. PROSPERO Protocol: CRD42019121304

Nodal dynamic models allow rapid reduced-order simulations of complex systems. This paper presents a publicly available system dynamic model of a molten salt reactor system with a topology of the Molten Salt Reactor Experiment (MSRE), in MATLAB/Simulink, building upon a model previously published and validated with MSRE data. It adds scaling of nominal power, dynamic representation of decay heat generation, a generic decay heat removal system, improved documentation, modularity, and test cases. One hour of system transient runs in less than 10 min on a laptop. This model is intended for first order engineering calculations, developing insights into system transient behavior, equipment sizing, parameter sensitivity studies. The model contains an easy to use toolkit which can be customized and expanded to describe any molten salt reactor system. Scenarios involving off-normal transients are presented. Relation between shutdown reactivity insertions, decay heat removal, core recriticality, and safe shutdown conditions are discussed.

The decision-making process in the Nuclear Power Plant (NPP) control room faces some challenges: operator incomplete knowledge, insufficient time for responding to the highly dynamic events, and a large number of indicators to monitor. Because of the complexity of the NPP system, it is hard to pre-plan all the failures/mitigative actions. An intelligent operator support system is vital to mitigate these shortcomings. In this paper, an AI declarative approach (Answer Set Programming (ASP)) is employed to represent our knowledge of the nuclear power plant in the form of logic rules. This represented knowledge is structured to form a reasoning-based operator support system. When an incident occurs, this ASP-based reasoning support system is demonstrated to be capable of fault identification (diagnosis), informing the operator of different scenarios and consequences, and generating the control options (decision making).

Peripheral vascular interventions (PVI) utilize iodinated contrast medium (ICM) to visualize intravascular lesions and guide therapy. The use of ICM carries a risk of postcontrast acute kidney injury (PC-AKI), which is increased in the elderly and in patients with chronic kidney disease (CKD). Furthermore, the risk of PC-AKI increases with the volume of ICM used. This paper reports a 94-year-old patient with CKD stage 4 who presented with chronic limb threatening ischemia. He underwent successful endovascular revascularization using a combination of CO2 and dilute ICM (total volume = 6.5 mL). The case demonstrates strategies to minimize ICM during PVIs.

Language identification (LID) is identifying a language in a given spoken utterance. Language segmentation is equally important as language identification where language boundaries can be spotted in a multi-language utterance. Language identification could be a trivial front-end process for real-time mixed-speech recognition applications. India is a multilingual country and mixing two languages in a single conversation is very usual. In this paper, we have experimented with two schemes for language identification in Indian regional language context as very few works have been done. Singular value-based feature embedding is used for both of the schemes. In the first scheme, the singular value decomposition (SVD) is applied to the n-gram utterance matrix and in the second scheme, SVD is applied to the difference supervector matrix space. We have observed that in both the schemes, 55–65% singular value energy is sufficient to capture the language context. We have also seen how these two schemes are preserving language context. In n-gram based feature representation, we have seen that different skipgram models capture different language context. We have observed that for short test duration, supervector based feature representation is better but with a longer duration test signal, n-gram based feature performed better. We have also extended our work to explore language-based segmentation, where we have seen that segmentation accuracy of four language group with ten language training model, scheme-1 has performed well but with same four language training model, scheme-2 has shown better accuracy. In a multilingual language setup, the language-based identification and segmentation will be useful to identify the language as well as the duration of its presence. Further, the language-specific model can be used to identify the speech.

In order to improve the classification performance of ship-radiated noise effectively, a comparative study of four multi-scale entropies is carried out by combining with grey relational degree (GRD) and a novel classification method for ship-radiated noise is proposed based on multi-scale reverse dispersion entropy (MRDE) and GRD, named MRDE-GRD. In this paper, MRDE is applied to the complexity feature extraction of ship-radiated noise under different scales, and GRD is used to identify different kinds of ship-radiated noise by calculating the GRD of the ship to be identified and reference ships. Experimental results show that the proposed MRDE-GRD classification method can effectively extract the complexity features of ship-radiated noise, and has better classification performance than the other three classification methods based on multi-scale permutation entropy (MPE), multi-scale weighted permutation entropy (MWPE) and multi-scale dispersion entropy (MDE) combined with GRD, named MPE-GRD, MWPE-GRD, and MDE-GRD. It is proved that the proposed classification method for ship-radiated noise is effective and achieves a recognition rate of 97.75%.

In this paper, inorganic semiconductor CdS nanorods (CdS-NRs) with strong visible-light absorption was used to modify hierarchically structured Ni-based MOF NMOF-Ni assembled from ultrathin nanosheets. It was found that the HER under simulated sunlight irradiation sharply increases 55.6 times (from 81 to 4500 μmolg−1 h−1) after modification of NMOF-Ni with 10 wt.% CdS-NRs. This enhanced performance originating from the CdS-NRs greatly improves the light absorption, and the imitate contact between NMOF-Ni and CdS-NRs stimulates the charge separation and migration. In addition, CdS-NRs/NMOF-Ni hybridized photocatalyst exhibits excellent photo-stability in hydrogen production due to the protection of NMOF-Ni, which can efficiently prevent the photo-corrosion of CdS-NRs. A direct Z-scheme electron transfer mechanism is proposed for the enhanced simulated sunlight photoreactivity of CdS-NRs/NMOF-Ni hydized photocatalyst towards hydrogen production.

The bifacial gain of East-West vertical and South-facing optimally-tilted bifacial solar farms are well established. One wonders if bifacial gain and the associated levelized cost of energy (LCOE) may be further improved by tracking the sun. Tracking bifacial photovoltaics (PV) system has advantages of improved temperature sensitivity, enhanced diffuse and albedo light collection, flattened energy-output, and reduced soiling. Monofacial tracking already provides many of these advantages, therefore the relative merits of bifacial tracking are not obvious. In this paper, we use a detailed illumination and temperature-dependent bifacial solar farm model to show that bifacial tracking PV delivers up to 45% energy gain when compared to fixed-tilt bifacial PV near the equator, and ~10% bifacial energy gain over tracking monofacial farm with an albedo of 0.5. An optimum pitch further improves the gain of a tracking bifacial farm. Our results will broaden the scope and understanding of bifacial technology by demonstrating global trends in energy gain for worldwide deployment.

The energy use intensity of wastewater treatment facilities has been increasing in recent decades in China. In this paper, data envelopment analysis is used to evaluate the energy efficiency of municipal wastewater treatment plants (WWTPs) in China. In the DEA model, the six input indicators were load rate, design scale, unit electricity consumption, sludge generation, actual treatment volume and accumulated electricity consumption, and the six outputs were COD, BOD, SS, NH3-N, TN and TP pollutant removals per amount of electricity consumption. A total of 4100 plants were assessed in China in 2018. The relative efficiencies of 14 plants at 1.0, with an average electricity consumption of 0.091 kWh/m3 compared to the national average consumption of 0.38 kWh/m3, served as a benchmark for the remaining inefficient plants. According to the Malmquist index results, during 2014–2018, on average, 40.54% of the WWTPs experienced productivity improvements, 71.24% of the plants increased their technical efficiency relative to the frontier, and 27.21% of the plants showed progress on the production frontier. Western areas in China consume a large proportion of renewable energy with higher energy efficiency levels, while central and eastern areas had lower energy efficiency trends and high pollutant emissions levels. The oxidation pond method has the highest comprehensive technical efficiency of 0.446, nearly eight times the average efficiency level. It is suggested that wastewater treatment industries should not only consider technical efficiency increases but also match their pollutant burdens and implementation of discharge standards with energy-saving targets.

Energy efficiency remains as the main mitigation factor to slow down the growth of energy consumption and related CO2 emissions, undoubtedly the major responsible for climate change. Gaining insights into the driving forces that make efficiency change is a keystone to define energy policies and examine pathways to sustainable development. To this aim, this paper proposes a pyramidal approach for the analysis and decomposition of energy intensity, the main global efficiency indicator, using the LMDI method. First, the effects related to supply and demand sides of the energy system are separated in Primary Energy Factor and final energy intensity, respectively. Then, supply side is further decomposed to progressively reveal structural effects associated to transformation processes and fuel types. The approach is applied to the most emitting and consuming nations (China, United States, European Union, India, Russia, Japan) to provide a meaningful cross-country analysis over the period 1995–2017. Results show that energy intensity gains have been mainly driven by widespread demand side efficiency improvements from 25% to 61%. Regarding the supply side, unfavourable structural changes due to electrification, up to 12% in China, have only been offset by transformation efficiency gains about 6% in developed countries. Consequently, emerging economies have worsened their energy sector efficiency as they thrive. Changes in fuel mixes have generally contributed to energy intensity reductions (up to 4%) mainly due to shifts from coal and nuclear power towards gas and renewables plants. The proposed methodology could help stakeholders to effectively analyse the energy system and to develop policies to reduce its environmental impact.

This paper analyses the role of sector coupling towards 2050 in the energy system of Northern-central Europe when pursuing the green transition. Impacts of restricted onshore wind potential and transmission expansion are considered. Optimisation of the capacity development and operation of the energy system towards 2050 is performed with the energy system model Balmorel. Generation, storage, transmission expansion, district heating, carbon capture and storage, and synthetic gas units compete with each other. The results show how sector coupling leads to a change of paradigm: The electricity system moves from a system where generation adapts to inflexible demand, to a system where flexible demand adapts to variable generation. Sector coupling increases electricity demand, variable renewable energy, heat storage capacity, and electricity and district heating transmission expansion towards 2050. Non-restricted investments in onshore wind and electricity transmission reduce emissions and costs considerably (especially with high sector coupling) with savings of 78.7€2016/person/year. Investments in electric power-to-heat units are key to reduce costs and emissions in the heat sector. The scenarios with the highest sector coupling achieve the highest emission reduction by 2045: 76% greenhouse gases reduction with respect to 1990 levels, which highlights the value of sector coupling to achieve the green transition.

Integrated Energy System (IES) has been proved to be able to effectively improve energy utilization and economic benefits. In the day-ahead dispatch of city-scale IES, electricity-gas interconnection is widely used to realize energy complementarity among regions, where the pressure regulation and electricity-heat-gas coupling in the gas gate station powered by Combined Heating and Power (CHP) device are usually excluded. Therefore, with the gas gate station centered, CHP fired energy hub linearization model, the optimized dispatching model of city-scale IES considering the flexibilities of city gas gate station and line packing is established in this paper where an Integrated Electricity and Gas System (IEGS) is running among regional Combined Cooling, Heating and Power (CCHP) systems, applying power and natural gas coupled energy flow algorithm. Results of case studies verify the potential of pipeline storage compared with gas storage tanks up to an 8.391% reduction on overall operation cost, a 14.366% improvement on renewable energy utilization and charging/discharging cycles reaching only 0.197 times of those of tanks, especially in areas with rich renewable energy. Besides, regulated by CHP fired energy hub which is worth constructing for its economic benefits and alleviation of peak power supply pressure, the average pipeline pressure proportional to stored gas volume increases by 5.885%, enhancing the flexibility of line packing. Moreover, this paper demonstrates that heating economy of gas boilers and electric boilers in comparison to gas turbines rises in turn with the increase of Gas-Electricity Price Ratio (GEPR). Lastly, Quasi Elastic Coefficient (QEC) is defined to describe multi-energy consumption sensitivity to Time-Of-Use (TOU) energy tariff, which is helpful in energy pricing and equipment scheduling.

The penetration of large-scale renewable energy puts an urgent demand on increasing power grid flexibility. From the power grid perspective, transmission congestion has become one of the bottle-neck factors limiting renewable energy integration. In the tradition, transmission topology is regarded to be unadjustable, and energy storage only plays an important role in the local area where it locates. To enhance the transmission system flexibility and relieve transmission congestion, this paper proposes a network-constraint unit commitment (NCUC) model considering battery energy storage transportation (BEST) and transmission switching (TS). This model is integrated with a novel indicator based BEST model and a TS model to minimize the overall operating cost. The benefits of BEST mobility and TS flexibility are quantitatively evaluated through compared with the traditional NCUC model. Based on the difference between the overall operating cost of unit commitment (UC) and NCUC, we quantitatively evaluated the flexibility provided by BEST and TS by the overall operating cost reduction. A case study on a modified IEEE RTS-79 system is provided to validate the effectiveness of the proposed model. The results show that the BEST and TS have a synergistic effect on enhancing power grid flexibility, which reflects in this study as the power grid operating economics improvement and renewable energy curtailment reduction. Besides, though the BEST and TS bring transmission system more losses, applying them into the system could relieve transmission congestion, which makes them valuable technologies to improve power system security.

The Air Pollution Prevention and Control Action Plan proposed in 2013 has contributed to the fossil fuel reduction in central heating, but the consumption of scattered coal in rural areas should not be overlooked as it accounts for nearly 50% pollutant emissions during the heating season. Air Pollution Prevention and Control Action Plan for Beijing-Tianjin-Hebei and Surrounding Areas was issued to solve the problem of scattered coal consumption and improve the heating energy structure in 2017. In this paper, an air quality-heating model is established to evaluate the air quality improvement potential and far-reaching influence of scattered coal consumption reduction in rural areas. Distinct from other air quality evaluation models, the proposed model is to evaluate the regional air quality related to the heating factors. The results indicate that the coal substitution policy can reduce PM2.5 concentrations in the heating season by about 20 μg/m3 in Beijing-Tianjin-Hebei and surrounding areas. Furthermore, predictions about the variation of PM2.5 concentration in the heating season are conducted, which indicate that the PM2.5 concentration of Beijing, Tianjin, Hebei and surrounding areas in 2030 will drop by 48%, 35%, 29% and 23% respectively compared to that in 2016. The reduction could be further enhanced to be 55%, 40%, 32% and 27% with the consideration of clean power development. This study is conducive to evaluate the clean heating technologies role in improving the environment and air quality.

This paper examines the interconnections between the power and transportation networks from a game theoretic perspective. Electric vehicle travelers choose the lowest-cost routes in response to the price of electricity and traffic conditions, which in turn affects the operation of the power and transportation networks. In particular, discrete choice models are utilized to describe the behavioral process of electric vehicle drivers. A game theoretic approach is employed to describe the competing behavior between the drivers and power generation units. The power-traffic network equilibrium is proved to possess a potential type structure, which establishes the properties of the network equilibrium. Moreover, the network equilibrium state is shown to be a welfare-maximizing operating point of the electric distribution network considering the spatial demand response of electric vehicle loads. A decentralized algorithm based on the optimality condition decomposition technique is developed to attain the equilibrium flow solutions. Numerical experiments demonstrate how the proposed framework can be used to alleviate both power and traffic congestion.