Emissions control policies under uncertainty and rational learning in a linear-state dynamic model

We compare the use of price-based policies or taxes, and quantity-based policies or quotas, for controlling emissions in a dynamic setup when the regulator faces two sources of uncertainty: (i) market-related uncertainty; and (ii) ecological uncertainty. We assume that the regulator is a rational Bayesian learner and the regulator and firms have asymmetric information. In our model the structure of Bayesian learning is general. Our results suggest that the expected level of emissions is the same under taxes and quotas. However, the comparison of the total benefits related to these policies suggests that taxes dominate quotas, that is, they provide a higher social welfare. Even though taxes have some benefits over quotas, neither learning nor ecological uncertainty affect the choice of policy, i.e., the only factor having such an impact is uncertainty in the instantaneous net emissions benefits (market-related uncertainty). Besides, the more volatile is this uncertainty, the more benefits of taxes over quotas. Ecological uncertainty leads to a difference between the emissions rule under the informed and the rational learning assumptions. However, the direction of this difference depends on the beliefs bias with regard to ecological uncertainty. We also find that a change in the regulator’s beliefs toward more optimistic views will increase the emissions.     

Low voltage second-order alpha function synapse

This paper introduces a Transimpedance Amplifier (TIA) design capable of producing an incremental input resistance in the ohmic range, for input signals in the microampere range, such as are encountered in the design of instrumentation for electrochemical ampero-metric sensors, optical-sensing and current-mode circuits. This low input-resistance is achieved using an input stage incorporating negative feedback. In a Cadence simulation of an exemplary design using a 180 nm CMOS process and operating with?±?1.8 V supply rails, the input resistance is 1.05 ohms and the power dissipation is 93.6 µW. The bandwidth, for a gain of 100 dBohm, exceeded 9 MHz. For a 1µA, 1 MHz sinusoidal input signal the Total Harmonic Distortion, with this gain, is less than 1%. The input referred noise current with zero photodiode capacitance is 2.09 pA/√Hz and with a photodiode capacitance of 2pF is 8.52 pA/√Hz. Graphical data is presented to show the effect of a photodiode capacitance varying from 0.5 to 2 pF, when the TIA is used in optical sensing. In summary, the required very low input resistance, at a low input current level (µA) is achieved and furthermore a Table is included comparing the characteristics and a widely used Figure of Merit (FOM) for the proposed TIA and similar published low-power TIAs. It is apparent from the Table that the FOM of the proposed TIA is better than the FOMs of the other TIAs mentioned.

     

Soft groups and normalistic soft groups

Soft set theory, proposed by Molodtsov, has been regarded as an effective mathematical tool to deal with uncertainties. In this paper, first we correct some of the problematic cases in a previous paper by Akta? and Çag˜man [H. Akta?, N. Çag˜man, Soft sets and soft groups, Inf. Sci. 177 (2007) 2726-2735]. Moreover, we introduce the concepts of normalistic soft group and normalistic soft group homomorphism, study their several related properties, and investigate some structures that are preserved under normalistic soft group homomorphisms.     

Bounded‐Input Control of the Quadrotor Unmanned Aerial Vehicle: A Vision‐Based Approach

In this paper, a bounded‐input controller is designed for the quadrotor vertical take‐off and landing unmanned aerial vehicle (UAV). Visual information is used to localize the aircraft with respect to its environment and an image‐based visual servo scheme is developed to navigate the motion of it. The visual features are selected from perspective image moments and projected on a rotated image plane, which simplifies the controller design. The flow of the features is used as the linear velocity information, and the controller assumes angular velocity and attitude information available for feedback. To design the controller, the dynamics of the quadrotor are decoupled into two parts: translational dynamics and rotational dynamics. First visual data are used to design a bounded‐input controller for the translational dynamics, and then a saturated controller is designed for the rotational dynamics. The boundedness of the controller increases the chance of keeping the visual features in the field of view of the camera. Furthermore, the controllers also cope with the unknown depth of the image, and the external disturbances. The complete stability analysis of the overall system is presented to show that all states are bounded and the error signals converge to zero asymptotically. Simulation examples are provided in both nominal and perturbed conditions which show the effectiveness of the proposed theoretical results.     

Anti‐Oxygen Leaking LiCoO2

LiCoO₂ is a prime example of widely used cathodes that suffer from the structural/thermal instability issues that lead to the release of their lattice oxygen under nonequilibrium conditions and safety concerns in Li‐ion batteries. Here, it is shown that an atomically thin layer of reduced graphene oxide can suppress oxygen release from Li_xCoO₂ particles and improve their structural stability. Electrochemical cycling, differential electrochemical mass spectroscopy, differential scanning calorimetry, and in situ heating transmission electron microscopy are performed to characterize the effectiveness of the graphene‐coating on the abusive tolerance of Li_xCoO₂. Electrochemical cycling mass spectroscopy results suggest that oxygen release is hindered at high cutoff voltage cycling when the cathode is coated with reduced graphene oxide. Thermal analysis, in situ heating transmission electron microscopy, and electron energy loss spectroscopy results show that the reduction of Co species from the graphene‐coated samples is delayed when compared with bare cathodes. Finally, density functional theory and ab initio molecular dynamics calculations show that the rGO layers could suppress O₂ formation more effectively due to the strong C? O_cathode bond formation at the interface of rGO/LCO where low coordination oxygens exist. This investigation uncovers a reliable approach for hindering the oxygen release reaction and improving the thermal stability of battery cathodes.     

Influence of TiN dopant on microstructure of TiB2 ceramic sintered by spark plasma

In this study, the impact of TiN as a sintering aid on the relative density and microstructure of TiB₂ ceramic was investigated. Monolithic TiB₂ and TiB₂ doped with 5?wt% TiN were sintered at 1900?°C for 7?min dwell time under the pressure of 40?MPa by spark plasma. The addition of TiN affected the microstructure of TiB₂-based sample considerably depicting the finer grains in the as-sintered ceramic. X-ray diffraction evaluation indicated that no interaction occurred between the initial materials. However, detail investigation by the map analysis and energy dispersive spectroscopy results revealed the formation of in-situ nano-sized hBN secondary phase in the TiN-doped TiB₂. In addition, TiN played a remarkable role on increasing the relative density of TiN-doped TiB₂ ceramic producing a nearly fully dense ceramic with relative density of 99.9% in comparison with the monolithic ceramic having 96.7% relative density.     

Parkinson’s Disease Detection Using Biogeography-Based Optimization

In recent years, Parkinson's Disease (PD) as a progressive syndrome of the nervous system has become highly prevalent worldwide. In this study, a novel hybrid technique established by integrating a Multi-layer Perceptron Neural Network (MLP) with the Biogeography-based Optimization (BBO) to classify PD based on a series of biomedical voice measurements. BBO is employed to determine the optimal MLP parameters and boost prediction accuracy. The inputs comprised of 22 biomedical voice measurements. The proposed approach detects two PD statuses: 0-disease status and 1- good control status. The performance of proposed methods compared with PSO, GA, ACO and ES method. The outcomes affirm that the MLP-BBO model exhibits higher precision and suitability for PD detection. The proposed diagnosis system as a type of speech algorithm detects early Parkinson’s symptoms, and consequently, it served as a promising new robust tool with excellent PD diagnosis performance.     

Spark plasma sintering of Al-doped ZrB2–SiC composite

This research presents the influence of Al addition on microstructure and mechanical behavior of ZrB₂–SiC ultra-high temperature ceramic matrix composite (UHTCMC) fabricated by spark plasma sintering (SPS). A 2.5?wt% Al-doped ZrB₂–20?vol% SiC UHTCMC was produced by SPS method at 1900?°C under a pressure of 40?MPa for 7?min. The microstructural and phase analysis of the composite showed that aluminum-containing compounds were formed in-situ during the SPS as a result of chemical reactions between Al and surface oxide films of the raw materials (i.e. ZrO₂ and SiO₂ on the surfaces of ZrB₂ and SiC particles, respectively). The Al dopant was completely consumed and converted to the intermetallic Al₃Zr and Al₄Si compounds as well as Al₂O₃ and Al₂SiO₅. A relative density of 99.8%, a hardness (HV5) of 21.5?GPa and a fracture toughness (indentation method) of 6.3?MPa?m^1/2 were estimated for the Al-doped ZrB₂–SiC composite. Crack bridging, branching, and deflection were identified as the main toughening mechanisms.