Elevated CO2 and high endogenous ABA level alleviate PEG-induced short-term osmotic stress in tomato plants

Elevated CO2 concentration (e[CO2]) alleviates the impact of drought stress on plants where abscisic acid (ABA) is involved. To explore the mechanisms by which tomato plants respond to short-term osmotic stress, Solanum lycopersicum cv. Ailsa Craig (AC), a transgenic line overproducing ABA (sp5), and an ABA-deficient mutant (flacca) were hydroponically grown under ambient CO2 (400 ppm) and e[CO2] (800 ppm) and then exposed to 10% or 15% (w/v) polyethylene glycol (PEG) 6000 for 24 h before transferring to PEG-free nutrient solution for 24 h. Under non-stress condition, e[CO2] decreased root hydraulic conductance (Kroot), which was overridden by high endogenous ABA in sp5 through increasing specific leaf area and root branching intensity. Basically, e[CO2] improved stress resistance through enhanced water status. PEG stress decreased stomatal conductance and osmotic potential in AC but these effects were less pronounced in sp5, which exhibited a stronger osmotic adjustment (OA) and improved plant fitness. A greater flexibility of hydraulic system and a reduced sensitivity of Kroot to ABA might confer sp5 a great ability to recover from PEG stress. On the contrary, high stomatal density, size and pore aperture of flacca rendered plants suffering severe stress. Moreover, the premise that PEG stress could mimic soil water deficit was the sufficient achievement of OA. Our results indicate that e[CO2] and high endogenous ABA level could improve osmotic stress resistance in tomato plants via osmotic and hydraulic adjustments

An adaptive acoustoelectric signal decoding algorithm based on Fourier fitting for brain function imaging

Acousticelectric brain imaging (ABI), which is based on the acoustoelectric (AE) effect, is a potential brain function imaging method for mapping brain electrical activity with high temporal and spatial resolution. To further enhance the quality of the decoded signal and the resolution of the ABI, the decoding accuracy of the AE signal is essential. An adaptive decoding algorithm based on Fourier fitting (aDAF) is suggested to increase the AE signal decoding precision. The envelope of the AE signal is first split into a number of harmonics by Fourier fitting in the suggested aDAF. The least square method is then utilized to adaptively select the greatest harmonic component. Several phantom experiments are implemented to assess the performance of the aDAF, including 1-source with various frequencies, multiple-source with various frequencies and amplitudes, and multiple-source with various distributions. Imaging resolution and decoded signal quality are quantitatively evaluated. According to the results of the decoding experiments, the decoded signal amplitude accuracy has risen by 11.39% when compared to the decoding algorithm with envelope (DAE). The correlation coefficient between the source signal and the decoded timing signal of aDAF is, on average, 34.76% better than it was for DAE. Finally, the results of the imaging experiment show that aDAF has superior imaging quality than DAE, with signal-to noise ratio (SNR) improved by 23.32% and spatial resolution increased by 50%. According to the experiments, the proposed aDAF increased AE signal decoding accuracy, which is vital for future research and applications related to ABI

Facial first impressions across culture : data-driven modelling of Chinese and British perceivers’ unconstrained facial impressions

People form first impressions from facial appearance rapidly, and these impressions can have considerable social and economic consequences. Three dimensions can explain Western perceivers’ impressions of Caucasian faces: approachability, youthful-attractiveness, and dominance. Impressions along these dimensions are theorized to be based on adaptive cues to threat detection or sexual selection, making it likely that they are universal. We tested whether the same dimensions of facial impressions emerge across culture by building data-driven models of first impressions of Asian and Caucasian faces derived from Chinese and British perceivers’ unconstrained judgments. We then cross-validated the dimensions with computer-generated average images. We found strong evidence for common approachability and youthful-attractiveness dimensions across perceiver and face race, with some evidence of a third dimension akin to capability. The models explained ~75% of the variance in facial impressions. In general, the findings demonstrate substantial cross-cultural agreement in facial impressions, especially on the most salient dimensions

AI of Brain and Cognitive Sciences: From the Perspective of First Principles

Nowadays, we have witnessed the great success of AI in various applications, including image classification, game playing, protein structure analysis, language translation, and content generation. Despite these powerful applications, there are still many tasks in our daily life that are rather simple to humans but pose great challenges to AI. These include image and language understanding, few-shot learning, abstract concepts, and low-energy cost computing. Thus, learning from the brain is still a promising way that can shed light on the development of next-generation AI. The brain is arguably the only known intelligent machine in the universe, which is the product of evolution for animals surviving in the natural environment. At the behavior level, psychology and cognitive sciences have demonstrated that human and animal brains can execute very intelligent high-level cognitive functions. At the structure level, cognitive and computational neurosciences have unveiled that the brain has extremely complicated but elegant network forms to support its functions. Over years, people are gathering knowledge about the structure and functions of the brain, and this process is accelerating recently along with the initiation of giant brain projects worldwide. Here, we argue that the general principles of brain functions are the most valuable things to inspire the development of AI. These general principles are the standard rules of the brain extracting, representing, manipulating, and retrieving information, and here we call them the first principles of the brain. This paper collects six such first principles. They are attractor network, criticality, random network, sparse coding, relational memory, and perceptual learning. On each topic, we review its biological background, fundamental property, potential application to AI, and future development.Comment: 59 pages, 5 figures, review articl

Acoustoelectric brain imaging with different conductivities and acoustic distributions

Objective: Acoustoelectric brain imaging (AEBI) is a promising imaging method for mapping brain biological current densities with high spatiotemporal resolution. Currently, it is still challenging to achieve human AEBI with an unclear acoustoelectric (AE) signal response of medium characteristics, particularly in conductivity and acoustic distribution. This study introduces different conductivities and acoustic distributions into the AEBI experiment, and clarifies the response interaction between medium characteristics and AEBI performance to address these key challenges.Approach: AEBI with different conductivities is explored by the imaging experiment, potential measurement, and simulation on a pig’s fat, muscle, and brain tissue. AEBI with different acoustic distributions is evaluated on the imaging experiment and acoustic field measurement through a deep and surface transmitting model built on a human skullcap and pig brain tissue.Main results: The results show that conductivity is not only inversely proportional to the AE signal amplitude but also leads to a higher AEBI spatial resolution as it increases. In addition, the current source and sulcus can be located simultaneously with a strong AE signal intensity. The transcranial focal zone enlargement, pressure attenuation in the deep-transmitting model, and ultrasound echo enhancement in the surface-transmitting model cause a reduced spatial resolution, FFT-SNR, and timing correlation of AEBI. Under the comprehensive effect of conductivity and acoustics, AEBI with skull finally shows reduced imaging performance for both models compared with no-skull AEBI. On the contrary, the AE signal amplitude decreases in the deep-transmitting model and increases in the surface-transmitting model.Significance: This study reveals the response interaction between medium characteristics and AEBI performance, and makes an essential step toward developing AEBI as a practical neuroimaging technique

Research progress on using biological cathodes in microbial fuel cells for the treatment of wastewater containing heavy metals

Various types of electroactive microorganisms can be enriched to form biocathodes that reduce charge-transfer resistance, thereby accelerating electron transfer to heavy metal ions with high redox potentials in microbial fuel cells. Microorganisms acting as biocatalysts on a biocathode can reduce the energy required for heavy metal reduction, thereby enabling the biocathode to achieve a lower reduction onset potential. Thus, when such heavy metals replace oxygen as the electron acceptor, the valence state and morphology of the heavy metals change under the reduction effect of the biocathode, realizing the high-efficiency treatment of heavy metal wastewater. This study reviews the mechanisms, primary influencing factors (e.g., electrode material, initial concentration of heavy metals, pH, and electrode potential), and characteristics of the microbial community of biocathodes and discusses the electron distribution and competition between microbial electrodes and heavy metals (electron acceptors) in biocathodes. Biocathodes reduce the electrochemical overpotential in heavy metal reduction, permitting more electrons to be used. Our study will advance the scientific understanding of the electron transport mechanism of biocathodes and provide theoretical support for the use of biocathodes to purify heavy metal wastewater

Biological current source imaging method based on acoustoelectric effect: A systematic review

Neuroimaging can help reveal the spatial and temporal diversity of neural activity, which is of utmost importance for understanding the brain. However, conventional non-invasive neuroimaging methods do not have the advantage of high temporal and spatial resolution, which greatly hinders clinical and basic research. The acoustoelectric (AE) effect is a fundamental physical phenomenon based on the change of dielectric conductivity that has recently received much attention in the field of biomedical imaging. Based on the AE effect, a new imaging method for the biological current source has been proposed, combining the advantages of high temporal resolution of electrical measurements and high spatial resolution of focused ultrasound. This paper first describes the mechanism of the AE effect and the principle of the current source imaging method based on the AE effect. The second part summarizes the research progress of this current source imaging method in brain neurons, guided brain therapy, and heart. Finally, we discuss the problems and future directions of this biological current source imaging method. This review explores the relevant research literature and provides an informative reference for this potential non-invasive neuroimaging method

Indoor Landscape

My works use stylized painting methods to represent the architectures of consumption, a reality flattened both literal and metaphorically. Through mechanical vision, the paintings explore, critique, and contemplate attitudes concerning consumerism and mass production; including the mechanization of the architectures of consumption, and how they reinforce habits. My works also portray the power of information transmission from unrevealed language and the painterly gesture that replaced the alphabet in non-places—a place, not a social or physical space, which lacks the traditional attributes of space. The writing that follows provides a theoretical framework for the motives behind my practice. Fragmented and variant structures richly colored and textured figures and daily situations characterize my paintings, which are influenced by traditional genre painting and culture. Additionally, I place my work within the tradition of abstract painting, and compare and contrast my work with other artists, both historical and contemporary

Recent advances in the application of ionic liquids in antimicrobial material for air disinfection and sterilization

Airborne transmission is one of the most unpredictable routes of infection. Nowadays, airborne diseases increase ever than before because of the complex living air environment. Apart from the inorganic particles, active microorganisms including bacteria, viruses, and fungi are incorporated in the pathogens acting as threaten to public health, which can hardly be treated by the traditional air purification methods based on adsorption. Therefore, effective filtration material with antimicrobial activity is demanded to solve the problem. Ionic liquids (ILs) are a category of salts that remain liquid at room temperature. The stable physico-chemical properties and extremely low vapor pressure make them suitable for a wide range of applications. Thanks to the numerous combinations of cations and anions, as well as the ability of inheriting properties from the parent ions, Ils are believed to be a promising industrial material. In recent decades, several Ils, such as imidazolium, pyridinium, pyrrolidinium, phosphonium, and choline, have been found to have antimicrobial activity in their monomeric or polymeric forms. This work focuses on the antimicrobial activity and safety of the latest types of ionic liquids, discussing the synthesis or manufacturing methods of Ils for air purification and filtration. Furthermore, possible applications of Ils antimicrobial materials in medical instruments and indoor environments are mentioned to encourage the scientific community to further explore the potential applications of Ils