On Control Systems of the Brain: A Study of Their Connections, Activations, and Interactions

Implementation of daily functions in humans crucially relies on both the bottom-up moment-to- moment processing of relevant input and output information as well as the top-down controls that instantiate and regulate goal-directed strategies. The current dissertation focuses on different systems of brain regions related to task control. We are interested in investigating, in detail, some of the basic activity patterns that different control systems carry during simple tasks, and how differences in activity patterns may shed new insight onto the distinctions among the systems\u27 functional roles. In addition, carefully coordinated interactions between brain regions specialized for control-related activity and regions specialized for bottom-up information processing are essential for humans to adeptly undertake various goal-directed tasks. Hence, another goal is to explore how the relationships among regions related to control and regions related to processing will change as result of top-down control signals during tasks. In Chapter 2, we applied the graph theory method of link communities onto the brain\u27s resting-state intrinsic connectivity structure to identify possible points of interactions among the previously defined functional systems, including various control systems. In Chapter 3, we conducted a meta-analysis of tasks to examine the distinct functional characteristics of control systems in task activation. Using a data-driven clustering analysis, we identified two distinct trial-related response profiles that divided the regions of control systems into a right frontoparietal and cinguloopercular cluster, which may be engaged in fine-tuning task parameters and evaluating performance, and a left frontoparietal and dorsal attention cluster, which may be involved in timely updates of trial-wise parameters as well as information processing. In Chapter 4, we explored the changes in functional relationships among selected systems during individual trials of a goal-direct task and found the presence of complex and dynamic relationships that suggest changes among the various functional systems across a trial reflect both continuous as well as momentary effects of top-down signals. Collectively, the studies presented here both contributed to as well as challenged previous frameworks of task control in an effort to build better understanding of the basic organization and interactions among the brain\u27s functional systems

Opinion Optimization in Directed Social Networks

Shifting social opinions has far-reaching implications in various aspects, such as public health campaigns, product marketing, and political candidates. In this paper, we study a problem of opinion optimization based on the popular Friedkin-Johnsen (FJ) model for opinion dynamics in an unweighted directed social network with $n$ nodes and $m$ edges. In the FJ model, the internal opinion of every node lies in the closed interval $[0, 1]$, with 0 and 1 being polar opposites of opinions about a certain issue. Concretely, we focus on the problem of selecting a small number of $k\ll n$ nodes and changing their internal opinions to 0, in order to minimize the average opinion at equilibrium. We then design an algorithm that returns the optimal solution to the problem in $O(n^3)$ time. To speed up the computation, we further develop a fast algorithm by sampling spanning forests, the time complexity of which is $O(ln)$, with $l$ being the number of samplings. Finally, we execute extensive experiments on various real directed networks, which show that the effectiveness of our two algorithms is similar to each other, both of which outperform several baseline strategies of node selection. Moreover, our fast algorithm is more efficient than the first one, which is scalable to massive graphs with more than twenty million nodes

Gold-Sensitized Silicon/ZnO Core/Shell Nanowire Array for Solar Water Splitting

Solar water splitting represents one of the most promising strategies in the quest for clean and renewable energy. However, low conversion efficiency, use of sacrificial agents, and external bias for current water splitting system limit its practical application. Here, a gold-sensitized Si/ZnOcore/shell nanowire photoelectrochemical (PEC) cell is reported for efficient solar water oxidation. We demonstrated gold-sensitized n-Si/n-ZnO nanowire arrays exhibited higher energy conversion efficiency than gold-sensitized p-Si/n-ZnO nanowire arrays due to the favorable energy-band alignment characteristics. Without any assistance from an external electrical source and sacrificial reagents, gold-sensitized n-Si/n-ZnO core/shell nanowire array photoanode achieved unbiased water splitting under simulated solar light illumination. This method opens a promising venue to cost-efficient production of solar fuels

Surface Plasmon Enhanced Light Trapping in Metal/Silicon Nanobowl Arrays for Thin Film Photovoltaics

Enhancing the light absorption in thin film silicon solar cells with nanophotonic and plasmonic structures is important for the realization of high efficiency solar cells with significant cost reduction. In this work, we investigate periodic arrays of conformal metal/silicon nanobowl arrays (MSNBs) for light trapping applications in silicon solar cells. They exhibited excellent light-harvesting ability across a wide range of wavelengths up to infrared regimes. The optimized structure (MSNBsH) covered by SiO2 passivation layer and hemisphere Ag back reflection layer has a maximal short-circuit density (Jsc) 25.5 mA/cm2, which is about 88.8% higher than flat structure counterpart, and the light-conversion efficiency (η) is increased two times from 6.3% to 12.6%. The double-side textures offer a promising approach to high efficiency ultrathin silicon solar cells

Selective Pressure to Increase Charge in Immunodominant Epitopes of the H3 Hemagglutinin Influenza Protein

The evolutionary speed and the consequent immune escape of H3N2 influenza A virus make it an interesting evolutionary system. Charged amino acid residues are often significant contributors to the free energy of binding for protein–protein interactions, including antibody–antigen binding and ligand–receptor binding. We used Markov chain theory and maximum likelihood estimation to model the evolution of the number of charged amino acids on the dominant epitope in the hemagglutinin protein of circulating H3N2 virus strains. The number of charged amino acids increased in the dominant epitope B of the H3N2 virus since introduction in humans in 1968. When epitope A became dominant in 1989, the number of charged amino acids increased in epitope A and decreased in epitope B. Interestingly, the number of charged residues in the dominant epitope of the dominant circulating strain is never fewer than that in the vaccine strain. We propose these results indicate selective pressure for charged amino acids that increase the affinity of the virus epitope for water and decrease the affinity for host antibodies. The standard PAM model of generic protein evolution is unable to capture these trends. The reduced alphabet Markov model (RAMM) model we introduce captures the increased selective pressure for charged amino acids in the dominant epitope of hemagglutinin of H3N2 influenza (R2 > 0.98 between 1968 and 1988). The RAMM model calibrated to historical H3N2 influenza virus evolution in humans fit well to the H3N2/Wyoming virus evolution data from Guinea pig animal model studies

Opinion Optimization in Directed Social Networks

Shifting social opinions has far-reaching implications in various aspects, such as public health campaigns, product marketing, and political candidates. In this paper, we study a problem of opinion optimization based on the popular Friedkin-Johnsen (FJ) model for opinion dynamics in an unweighted directed social network with n nodes and m edges. In the FJ model, the internal opinion of every node lies in the closed interval [0, 1], with 0 and 1 being polar opposites of opinions about a certain issue. Concretely, we focus on the problem of selecting a small number of

Influence of CO₂ Curing on the Alkali-Activated Compound Mineral Admixtures’ Corrosion Resistance to NaCl Dry–Wet Alternations

In this study, the influence of CO2 curing on the corrosion resistance of reinforced alkali-activated compounds is investigated. Fly ash (FA) and blast furnace slag powder (BFS) are used as mineral admixtures. The specimens were subjected to dry–wet alternations with 3% NaCl, used to simulate a concrete structure under a corrosion environment. The ultrasonic velocity, mass loss rate, and electrical characteristics (such as electrical resistance, AC impedance spectra, and corrosion area rates determined by Tafel curves) are utilized to determine the degree of corrosion. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) are used to analyze the corrosion mechanism. Results show that the corrosion resistance is decreased by the addition of FA but improved by CO2 curing. When CO2 curing is provided, the addition of BFS shows a higher enhancing effect on the corrosion resistance than that of FA. The equivalent circuit diagram of reinforced alkali-activated compound mineral admixtures obtained by AC impedance spectra is composed of three electrical elements (electrical resistance and capacitance in parallel) in series. The X-ray diffraction results show that adding BFS and CO2 curing can decrease the rust’s iron oxides on the steel bars’ surface. Finally, as found in the SEM photos, BFS and CO2 curing can effectively improve the compactness of specimens. Meanwhile, the roughness of hydration is increased by CO2 curing

Effectiveness of Vegetable Oils as Rejuvenators for Aged Asphalt Binders

Traditional rejuvenators normally have a great deal of heavy fuel oils to supply the light oil component of asphalt binders, which decreases throughout a long-term aging process. However, heavy fuel oils can easily volatilize at a high recycling temperature (above 180°C), and this leads to a limited portion of reclaimed asphalt pavement (RAP) materials utilized in the recycled asphalt mixture (with a recycling rate less than 30%). Vegetable oils are rich in unsaturated fatty acids, which are similar to the light oil components, and have a better temperature resistance. Therefore, there is potential that vegetable oils can be utilized to recover the aged asphalt binder based on the asphalt rejuvenating mechanism. In this study, two rejuvenators with waste cooking vegetable oils (corn oil and soybean oil) to replace heavy oils and a commercial rejuvenator were used to recover the aged asphalt (extracted from RAP materials) with different ratios (by weight of asphalt) of 2, 4, 6, 8, and 10%. Dynamic shear rheometer (DSR) and rotational viscosity (RV) tests were used to evaluate the physical properties of the recovered asphalt binder. The low-temperature performance of the recovered asphalt binder was also evaluated by the bending beam rheometer (BBR) test. The laboratory tests and statistical analysis of variance (ANOVA) results show that the vegetable oil rejuvenators can effectively decrease the viscosity and stiffness of aged asphalt binder, which is beneficial for both fatigue and low-temperature cracking resistance. Furthermore, the rejuvenator can lower the viscosity and stiffness of the aged asphalt binder with a larger amount of vegetable oil. Overall, the vegetable oil content (6% to 8%) in the rejuvenator is proposed for recovering the aged asphalt binder in consideration of the rutting resistance under high temperatures

One plus one greater than two: high-performance inverted planar perovskite solar cells based on a composite CuI/CuSCN hole-transporting layer

The low-cost and stable inorganic p-type semiconductor copper(i) iodide (CuI) is a promising hole-transporting layer (HTL) material for inverted planar perovskite solar cells (PSCs). However, the power conversion efficiencies (PCEs) of inverted planar PSCs based on CuI HTLs reported so far are not satisfactory and far behind those of their organic counterparts. Herein, we demonstrate a simple but effective approach to improve the performance of inverted planar PSCs based on the CuI HTL through the incorporation of copper thiocyanate (CuSCN) into the CuI HTL. As compared to pristine CuI, the introduction of CuSCN significantly improves the quality of the film, resulting in a smooth and uniform film while maintaining relatively high electrical conductivity. As a consequence, the champion device based on the composite CuI/CuSCN HTL affords an impressive PCE of 18.76% under full sun illumination (100 mW cm(-2), AM 1.5G), which is substantially higher than the corresponding values of the respective devices containing pristine CuI (14.53%) and CuSCN (16.66%). This value is one of the highest efficiencies reported thus far for CuI- and CuSCN-based HTLs in PSCs. This work demonstrates the great potential of low-temperature solution-processed CuI/CuSCN composites as hole-selective layers for low-cost and efficient PSCs as well as other optoelectronic devices

Ultrahigh Adsorption Capacity Zirconium-Magnesium Composite Oxide Nanoclusters Remove Malachite Green from Aqueous Media

The environmental pollution caused by organic dyes has damaged serious harm to human life. Hence, a series of Zr-Mg composite oxide nanoclusters with different metal ratios were synthesized by solvothermal method for adsorption of malachite green in aqueous solution. The optimal adsorbent with Zr/Mg metal molar ratio of 1 : 2 presented good adsorption performance, which adsorption capacity reached 12647.60 mg/g, and removal rate of malachite green reached more than 99%. These adsorbents were characterized by X-ray diffraction, Fourier-transform infrared spectra, nitrogen adsorption-desorption, scanning electron microscope, transmission electron microscope, and other methods. Influence of initial concentration of malachite green solution, pH, adsorption temperature, and contact time on absorption efficiency was investigated through batch experiments. Pseudo-second-order kinetic model can well describe the adsorption kinetic data. The three-parameter Sips isotherm model was more suitable for predicting the experimental results than Langmuir and Freundlich, and the adsorption process was endothermic